Building With Drones: outdoor experiments on lightweight structures

BUILDING WITH DRONES:

OUTDOOR EXPERIMENTS ON LIGHTWEIGHT STRUCTURES Independent Research Thesis 2015 - Melbourne School of Design Student: Coralie Ming - Supervisor: Alberto Pugnale

ABSTRACT This thesis is about the outdoor possible use of small Unmanned Aerial Vehicles (UAV) - or drones - for architectural applications. So far, drones have been tested in laboratories as enclosed space allows for safe and precise navigation. This thesis intends to take the flying robots out of the laboratories and test how they can perform autonomously in an outdoor context to build a small cable beam structure. This kind of tensile structure is adapted to a drones’ building process for its lightness as the machine is unable to carry heavy loads.

In this research thesis, autonomous building process is achieved by remotely sending trajectories to the drones. Built with points defined by georeferenced positions and relative height to the ground, these trajectories are then autonomously executed by the drone to weave tensile structures. Taking the drones out of the laboratories implies adding a significant amount of uncertainty to the building process and challenges the architects to integrate these limitations both in conceptual design and building process.

Doing so is a step further towards real-world scenarios which could open up a new possibilities in the architectural field.

The thesis firstly provides the background of construction and robotics, secondly presents the experimentations to test the system and the drone’s behavior in an outdoor context and finally speculates on the future of drones in architecture. Videos showcasing the prototypes’ building processes is submitted along with this text.

Table of Contents INTRODUCTION PART 1: THESIS TOPIC AND BACKGROUND 1.0 INNOVATION IN CONSTRUCTION 1.1 Non-standard innovators in construction 1.2 Industrialisation and standardisation: Machines and automation on construction sites 2.0 FROM CONSTRUCTION TO DIGITAL FABRICATION 2.1 Digital materiality: Computing matter and architecture 2.2 Architects become makers: Towards a more precise control of materialisation 2.3 Mass customisation challenging standard serial production 2.4 Towards the future: The trends of digital fabrication 2.5 Limited digital fabrication: Towards aerial construction 3.0 BUILDING WITH DRONES 3.1 Utopia meets reality 3.2 Drones in architecture 3.3 Drones’ uses in other fields 3.4 Building with drones: General opportunities and limitations 3.5 State of the art in building processes

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PART 2: BUILDING WITH DRONES: EXPERIMENTS 4.0 UAV HARDWARE 4.1 Hovering flying machines 4.2 Quadrotors’ requirements 4.1.3 Flying principles 4.3 Positioning systems for autonomous flight 4.4 Machine customisation 5.0 SOFTWARE: ENABLING AUTONOMOUS BUILDING PROCESS 5.1 Strategies to achieve autonomous building process: 5.2 The Design of the robotic process 5.3 Data conversion: Between XYZ and geographic coordinates 5.4 Tool ecology: Input and extract data 6.0 TESTING THE SYSTEM’S PRECISION 6.1 Elements altering the precision 6.2 Learning from the experiments: Autonomous flight behavior 6.3 Autonomous flight behavior: Measuring inaccuracy 6.4 Digital VS real space: An imprecise global positioning system 6.5 Prototyping: Limitations in real world experiments 7.0 OUTDOOR BUILDING EXPERIMENTATIONS 7.1 Designing and building with imprecision 7.2 Experiment 1: Surface structure 7.3 Experiment 2: Cable beam structure 7.3.1 Reaching the limits of the gps system 7.4 Experiment 3: Cable beam bridge

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PART 3: TOWARDS FUTURE APPLICATIONS 8.0 BROADENING THE ARCHITECTURAL POSSIBILITIES 8.1 Building remotely 8.2 Mixing technologies: towards a hovering world 8.3 Robotic intelligence: Swarm and 3d mapping

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CONCLUSION Bibliography Bibliography: a subjective conceptual map Images’ sources

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Figure 1: The Fall of Icarus, Jacob Peter Gowy (after Rubens’ original sketch), Oil on Canvas, 1637

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Introduction Flying is a human dream. In the Greek mythology, the architect and craftsman Daedalus, inventor of the labyrinth, ingeniously used wax and feathers to build wings for his son, Icarus, and himself to escape from Crete. The young Icarus aimed for the sun but the wax of his wings melted and he fell into the sea. (Graff, 1993) It may be from this moment that architecture and flight, two seemingly opposite terms, fed the architectural theory for Centuries, from Leonardo da Vinci to Archigram.

More recently, flying architecture shifted from utopia to reality when small aerial vehicles (or drones) have been tested not as a mean to suspend a building in the air, but rather as a new tool in the construction process (Gramazio, Kohler & D’Andrea, 2013). This shift is the result of the development of computers increasingly automating the design and construction processes during the last 50 years and opened up a brand new field of possibilities for architecture; the so-called digital fabrication. Being at its embryonic stage, this new process is still in need of real and meaningful applications in the architectural field, but robots have fundamentally changed industrial production and they will probably have a similar effect upon architecture. Digital fabrication is only 15 years of age and although it has clear limitations (inability to work at architectural scale and on construction site) it also has qualities that could overcome the traditional limitations of construction processes. In fact, new machines’ technology such as the drones could be the answer to the issues of scaffolding, form work and material waste.

The aim of this thesis is to explore what could be the use of drones in building processes by using a problem solving approach. So far, drones have only been tested in laboratories, safe and precise spaces to fly, but how will they behave when flying and building autonomously in an outdoor environment? Will they cope with the inherent uncertainty of the real world? This thesis intends to explore these questions along with developing an outdoor autonomous navigation process. Doing so, automation would be finally available on-site and human intervention relegated to a remote and off-site position. Demonstrating that flying machines are able to build remotely and autonomously would breathe new air to architecture and open up new architectural possibilities.

The thesis firstly provides the background of construction and robotics, secondly presents the experimentations run to build the structures and finally speculate on the future of drones in architecture.

Videos showcasing the prototypes’ building processes is submitted along with this text.

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PART 1:

THESIS TOPIC AND BACKGROUND

1.0 INNOVATION IN CONSTRUCTION The introduction of robotics and drones in the architectural field is part of a longer history of industrialisation and automation in the building site (Bock & Langenberg, 2014). It is the result of the convergence of disciplines going beyond the architectural borders such as engineering, computer sciences and mechatronics. In the last fifteen years, the ongoing crossdisciplinary approach to architecture developed a new branch of construction/production: the so-called “digital fabrication”, a process including flying robots.

Charles Jencks in the Introduction to Cecil Balmond’s book “Informal” states that “Whenever there is a revolution, or fast change, in architecture, professional barriers break down as specialists exchange roles. Architects become sculptors, engineers become designers, artists turn into architects, and all these job description become fuzzy. New ideas, creativity and excellence in design emerge when barriers are momentarily broken in order to be reformed in new configurations” (Balmond, 2007). This thesis advocates that we are indeed in moment of fast change in architecture powered by the machines’ and computation fast evolving development. Robots and flying machines are part of the inventive edge that is moving architecture.

Figure 2-3: Salginatoble Bridge, Robert Maillart, 1929

1.1 Non-standard innovators in construction Throughout history, great innovators in the architectural field were also more than architects. One of the Renaissance Masterpieces, the Dome of Florence, is one of many example.

Ghiberti and Brunelleschi to whom the Dome is attributed were switching professions from goldsmith to sculptor and artist to architect. Since then, it happened countless times, producing innovators such as Eiffel, Tatlin and Le Corbusier (Balmond, 2007).

In this circle of ground-breakers we also find a specific category of architects who also are builders. Their deep understanding of building process and materiality coupled with architectural design produced unique pieces of architecture. The Swiss engineer, architect and builder Robert Maillart is one of them.

At the beginning of the 20th Century, he revolutionised the use of reinforced concrete only a few years after Hennebique’s introduction of the material in Switzerland in 1895 (HU, 2006). He designed and built a series of bridges across the country gradually optimising his techniques to achieve the best from the material properties. His designs are fluid and the variation of thickness structurally expresses the compressive forces of the geometries. Today, Robert Maillart’s structures

Figure 4-6: Palazzetto dello Sport, Pier Luigi Nervi, Roma, 1957 p10

are considered to be masterpieces within the engineering field

and the American Society of Civil Engineers has selected the Salginatobel bridge (see figure 3-4) as a “world monument” (Pedreschi 2008). Another example of innovating architect-builder is Pier Luigi Nervi, who along with Heinz Isler, Felix Candela, and Eduardo Torroja developed form resistant structures in the course of the 20th century. Nervi developed a range of new on-site building processes such as used for the Pallazzetto dello Sport in Rome (see figure 5-7) . The concrete panels are cast and assembled on site in order to achieve the best structural and architectural result for a relatively low cost (Pedreschi, 2008). These examples show that multi-disciplinarity in building process as much as in architectural knowledge resulted in great contribution to the architectural history.

1.2 Industrialisation and standardisation: Machines and automation on construction sites Along with innovators design also follows technology. Historically, technological change has always driven innovation in design (Barkow, 2014) and machines have always been crucial constructive facilitators (Navedtra, 2010) to turn architecture from drawings to reality. The construction field can be defined as “the art of transforming material to architecture“ (Gramazio & Kohler, 2014). The basic mechanical principles of levers, block, tackle, inclined plane and screw gears were mastered around year 0 and machines evolved from being very simple Archimedes’ inventions, to gaining complexity with inventors such as Da Vinci and Bruneleschi in the end of the Middle Age, until the emergence of engineering in the 18th Century. (Addis, 2007) Machines prevailing importance in the construction field comes from the Industrial Revolution in Europe where they embodied fast change. Along with the development of transport infrastructures, construction sites shifted from a localised industry into a national and heavily mechanised one (Bock & Langenberg, 2014). The demographic growth called for an urgent need for dwellings and mass-produced building elements emerged as man made traditional materials gave way to steel and glass. As a result of the Industrial Revolution, a large amount of standardised building elements were increasingly becoming the norm. Their production require simple and repetitive tasks well cut for low skilled laborers but most importantly for machines.

Within a couple of Centuries, machines became automated, enhanced with information technology. Building elements started to be successfully prefabricated in factories in the 80’s by Japanese companies such as Sekisui House, Toyota Home and Pana(sonic)Home (Bock & Langenberg, 2014). This resulted in the first wave of digital automation being a high standard, precise and fast production (White & al., 2014).

However due to the nature of buildings (i.e. size, weight and fixed location) the possibility of fully manufacturing complex buildings off-site is limited. Today there is still a lack of a technologically adequate and integrated manufacturing technology for the construction site (Linner, 2013). Some mono task robots appeared on site mainly in Japan in the late 70’s, early 80’s but the development of these machines were quickly aborted being too costly and lacking effectiveness (Bock & Langenberg, 2014). This thesis is part of this field of research and intends to explore the possible on-site uses of digital fabrication and more specifically flying robots in the building processes.

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2.0 FROM CONSTRUCTION TO DIGITAL FABRICATION When programing meets construction a brand new field of possibilities breaks the traditional boundaries of construction processes and materiality gets enriched with digital characteristics (Gramazio & Kohler, 2008) During the last 30 years, the development of computers has been increasingly automating not only the factory production but also the design process in the architectural field. Computer Aided Design (CAD) freed designers from Cartesian space (Dunn, 2012) but until the recent development of 3d printers, cnc routers, laser cutter, robotic arms and drones, digital design and materiality were two antagonists worlds; the digital vs the material. Digital fabrication successfully filled the gap between digital design and materiality allowing for a computed based flowing workflow from design to fabrication. However, if digital fabrication opens up a brand new field of automated possibilities to construction, it is still mainly an off-site method having difficulties coping with the architectural scale.

2.1 Digital materiality: Computing matter and architecture At the dawn of Post-Modernism, digital design emerged with the development of computers. The 90’s were galvanised by the technological novelty of the possibility to digitally draw nonorthogonal shapes, previously impossible to draw on a sheet of paper (Carpo, 2009). Designers digitally produced a whole range of unbuildable shapes and digital design was highly criticised for dematerialising architecture.

Indeed Antoine Picon in “Digital Architecture and the Poetics of Computation” states that: “In architecture the poetics of computation have not yet fully developed. Heretofore, digital architecture has exhausted itself, intoxicated by the possibilities of generating complex geometries” (Picon, 2004).

Emerged in the late 90’s, with experiments by Bernard Cache and Patrick Beaucé (see figure 8-9), digital fabrication filled the gap between digital design and reality.

By merging material and data, two seemingly antagonist terms, the robots blur the boundaries between design and construction. Whereas still being at a very embryonic stage, digital fabrication is a fast evolving field and within a decade it has become the norm within architecture school to use laser cutter, cnc router and 3d printers.

2.2 Architects become makers: Towards a more precise control of materialisation Digital fabrication allows the architect to have control over the production of their architecture. The smooth workflow made possible by the file-to-factory process allows the architect to overview the materialisation of design, from the first sketch to final production. This new construction method is generating a new era of architects being to some extent back to being the pre Albertian Masterbuilder. Alberti was the first to introduce the concept of task division that is now being called into question by digital architecture (Carpo, 2009). Indeed, the craft is back to the architects’ daily routine after having been dissociated for Centuries ever since Alberti claimed in the 15th Century: “architect should stop making things, and they should design things instead” (Alberti, 1966).

Digital fabrication is also more precise in the way it handles data from design to production. The information going from CAD to the production is a unified language p12

and robots materialise the code. This process is referred to as the “second digital age” where data and material, programming and construction are interwoven (Gramazio & Kohler and Willmann 2014). Both concepts of the architect gaining greater control over the making process and the unified file-to-factory, are experimented in this thesis.

2.3 Mass customisation challenging standard serial production One of the fundamental difference between standardised construction and digital fabrication is the notion of “mass customisation”. Appeared in 1987 for the first time, the term expresses the faculty of digitally controlled machines to make individual products as economically as comparable mass-produced articles (Davis, 1987). In other words, it will take the same amount of time and energy to a machine to make a 1000 times the same movement as a 1000 different movements (Dunn, 2012). This ability challenges the serial production developed by the Industrial Revolution as stated

by Mario Carpo: “It has made it possible to overcome not only the design principles of Modernism but also their standardised industrial forms of production” (Carpo, 2008). The Pike Loop by

Figure 7-8: CNC Milling Experiments, Bernard Cache & Patrick Beaucé, 1997

Gramazio and Kohler is one of the architectural application of an industrial robot (See figure 10-11). Each brick is layered in a different position and direction and such a precise and nonrepetitive task, would not have been possible without being performed by a robot. Mass customisation, or the ability of the machine to precisely perform non-repetitive tasks is one of the asset of the use of drones in the future of construction.

2.4 Towards the future: The trends of digital fabrication a. Optimised building elements and sustainability: Digital Design and manufacturing can be environmentally sound. If additive construction technique, material optimisation software and customised building elements allow the architect to have a better control over the material it could be used to build in an economic way. As experimented by architects such as Frei Otto or Buckminster Fuller, their approach to design informed a better discussion between the material properties and the form. Following their example, the MIT research group Mediated Matter, led by Neri Oxman, introduced a more intelligent approach to materiality (Carpo 2008) aiming for maximal performance with minimal resources (Oxman, 2012) such as a graduated mater with a varying material density responding to the amount of structural stress (See figures 145).

Figure 9-10: Pike Loop, F. Gramazio & M. Kohler, New York, 2009 p13

b. Autonomous machines: feedback loops and non-linear work flow Machines’ evolution is now heading towards a constant interaction with their environment (Lloret Kristensen & Al. 2013). The addition of sensors feeding the computer with information from the site and material reality introduces a feedback loop process from the script to the reality and vice versa. One example of this feedback loop is the “smart dynamic casting” (see figures 12-13), a responsive slip-casting of concrete that measures when the concrete is cured and automatically moves the mold up for another layer. This is a great step towards intelligent digital fabrication. Machines will finally be truly autonomous when they will be able to communicate with matter and their environment.

2.5 Limited digital fabrication: Towards aerial construction Even if design methodology, introduced by digital fabrication as a complex and refined robotic process widen the architectural possibilities, there are clear limitations preventing it to be widely used in on-site construction processes.

The first limitation is scale. Digital fabrication machines are limited in the breadth of their application and are confined to produce elements genuinely smaller than the machine itself.

Indeed, cnc router, 3d printers and laser cutter are machines being proportionally larger than their products. Lately 3d printers have been scaled to be able to print full scale houses but for economic and practical reasons, it is unlikely that it becomes the norm. Another limitation for the smaller scale machines such as robotic arms is their difficulty to autonomously navigate in a construction site. The uncertainty of the ground situation inherent to the building process prevents the machines to safely move through space. In the example of the Pike Loop (see figure 10-11) the machine is mounted on rails to extend its reaching limits but only for a few meters.

Drones don’t have such limitations. Being freed from the ground constraints, the flying machines are able to autonomously access any point in space. The scale of the machine allows it to build structures significantly bigger than itself as long as the weight remains low. For these reasons, this thesis advocates that flying robots are the best solution for on-site digital fabrication.

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Figure 11-12: Dynamic Slip Casting, Gramazio Kohler Research 2012-15

Figure 13-14: Functionaly graded concrete, Mediated Matter (MIT) 2013

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CONSTRUCTION COSNTRUCTION MACHINES

THEORY ORGANIC UTOPIA

INNOVATION IN CONSTRUCTION

MAKING & MAKERS

DRONES AERIAL ARCHITECTURE

NON STANDARD

DIGITAL FABRICA

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CAD PARAMETRIC MODELING

ENVIRONMENT ANALYSIS FORMFINDING STRUCTURAL ENGINEERING

OPTIMIZATION

PROGRAMMING Information flows from design to materiality with the same language

DIGITAL MATERIALITY

INDUSTRIAL PRODUCTION

S

MECHATRONICS

MASS CUSTOMIZATION

ATION

AUTOMATION ROBOTS

STANDARDIZATION

Figure 15: a cross-disciplinary field

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Figure 16-17: Instant City, Peter Cook, Archigram, 1968

Figure 18-19: Palmtree Island, Haus-Rucker-Co, 1967-1977 p18

3.0 BUILDING WITH DRONES 3.1 Utopia meets reality Through history, but also mythology and utopias, there is a strong connection between architecture and flying. From Icarus to Da Vinci, humans and architects developed flying machines to escape gravity. Later on, Modernism explored the illusion of lightness with architect Oscar Niemeyer and his Museum of contemporary Art, Niteroì, or the Theme Building LAX. The 60’s and 70’s were also quite fruitful in imagining Utopian cities and nomadic way of life implying flying architecture.

Archigram or the Viennese Haus Rücker imagined whole new ways of living in the air. It is only more recently that flying architecture shifted from utopia to reality with the appearance of small aerial vehicles, not as a mean to suspend a building in the air, but as a new tool in the construction process.

3.2 Drones in architecture In the last 5 years, flying robots have been at the center of some of the research in the architectural field. Drones are enjoying an increasing popularity as the technology is evolving towards a variety of uses not only in architecture. As stated by Walter Benjamin: The technology does not develop in isolation from its cultural context; it emerges out of a process of differentiation with all the associated social, political and economic interaction (Benjamin, 2010).

Freed from the limiting spatial boundaries intrinsic to other computer-controlled machines such as cnc router, 3d printers or laser cutters, they are good candidates to work on full scale architectural construction (D’Andrea & Al., 2013). Large flying machines such as helicopters are already in construction processes to carry heavy loads to places inaccessible by the ground. More recently, the Aerial Robotic Construction Assembly System (Arcas, 2015) planed to equip helicopters with robotic arms for building purposes. However these experiments are rather adapted to heavy duty work, not adapted to precise modes of assembly.

The first groundbreaking experiment allying small UAV in autonomous building processes was the “flight assembled architecture” by the research groups “Gramazio Kohler Research” and the “institute for dynamic systems and control” (ETH). Thousands of bricks were layered by autonomous quadrotors in a non-standard way to build a 6m high installation and blurred line between utopia and reality, the thinkable and the feasible (Kohler, 2012 ).

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3.3 Drones’ uses in other fields Flying machines are slowly moving towards a wide range of uses across numerous disciplines. This is a selection of these existing uses that will probably get commonly accepted in the future.

Aerial Images Aerial imaging ability for personal or commercial uses (2011, see figure 20).

Transportation DHL, Amazon, Domino Pizza and other national post offices are testing delivery options with drones. The process is at a very early stage but we are eventually getting closer to this kind of applications (2013, see figure 23) Agriculture Precision agriculture/remote farming. It scans the fields, rebuild a 3d map of it, analyze the production, individually treat diseases (2015, see figure 25) Search and rescue missions Flying machines are equipped with infrared to find people in avalanches (2015, see figure 26) or buildings are inspected with a crash-happy drone after earth quakes.

Machines are sent to replace human if it is unsure that the building is safe (2013, see figure 24) Protecting Wildlife Monitor wildlife populations and chart land use changes (2013, see figure 28) Architecture Building inspection Surveying buildings is an expensive and time consuming effort considering that inspectors need to be physically transported to the inspection site. Drones are increasingly making this process easier by flying around and filming the buildings, while images are remotely analyzed. (see figure 27) 3d mapping of land and buildings.

It can be done indoor or outdoor and helps architects to quickly scan buildings to get maps specially if the site has no existing accurate architectural drawing. This process is excellent for non standard 3d elements. (see figure 21-22)

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Figure 29: Flight Assembled Architecture, 2011-2012

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3.4 Building with drones: General opportunities and limitations a. Opportunities

b. Limitations

Flying machines, unlike other robots,

Flying robots are unable to carry heavy

are not bound to the ground and are

loads and have a limited flying time. They

free to navigate in an almost unlimited

are incapable of absolute precision in the

space. The machines have six degrees

building process.

of freedom (+/-xyz), rotation (roll, yow, pitch) and velocity. This implies an almost unlimited reach.

Consequences for architecture: Flying machines are free to build, weave and fly regardless of the ground situation.

Their scale is substantially smaller that the intended built project which enlarges the design possibilities. Structures can be built without scaffold or crane in hostile or inaccessible spaces. Being computer-controlled they can build non-standard elements autonomously. They can build either individually or in cooperation with other robots, humans or drones. The main issues are: imprecision which implies a need for a greater tolerance in the design-construction process and weight which means that they can only assemble lightweight material systems or very small building elements.

Assembling building from the air questions the idea of tectonics and implies a profound rethinking of material and building processes.

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3.5 State of the art in building processes 5 research projects using flying machines in a building process (in chronological order)

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Research Year: 2011-12 Research Project Flight assembled architecture Research Team: Gramazio Kohler Research & Institute for Dynamic Systems and Control (ETH) J. Willmann, F. Augugliaro, T. Cadalbert, R. D’Andrea, F. Gramazio and M. Kohler Research Aims “Build an art installation that is one of the first structures autonomously built by flying vehicles” (Gramazio & al., 2012)

Research Year: 2011-12 Research Project Construction of Cubic Structures with Quadrotor Teams Research Team: Grasp Laboratory (U.Penn) Q. Lindsey, D. Mellinger, V. Kumar

Pros No Scaffold needed Relatively precise bricks’ layering Free-formed geometry Autonomous navigation Swarm behavior File-to-factory

Pros Magnets nodes cancels the uncertainty of aerial construction processes Autonomous swarm behavior Structurally sound outcome

Pros No need to carry heavy lo Swarm behavior Library of building eleme Autonomous navigation Swarm behavior Tensile elements

Cons Indoor (easier to manage drones’ path inside a laboratory controlled environment) No heavy loads (foam bricks) Scale 1:100 (scaling up the model would make impossible for drones to carry the loads)

Cons Scale (scaling up the model would make impossible for drones to carry the loads) Indoor (easier to manage drones’ path inside a laboratory controlled environment)

Cons Indoor (easier to mana laboratory controlled env At that stage no clear arch

Possible future applications Drones involved in additive fabricating processes.

Possible future applications Drones building remotely self-standing structures.

Possible future applica Drones weaving tensile an

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Research Aims “To assemble 2.5-D structures from simple structural nodes and members equipped with magnets. Quadrotors equipped with grippers autonomously pick up, transport, and assemble the structural elements.” (Lindsey & al., 2012)

Research Year: 2012 Research Project: Building Tensile Structur Research Team: Gramazio Kohler Researc Systems and Control (ET F. Augugliaro, A. Mirjan, F R. D’Andrea Research Aims: “To define basic buildin assembly of tensile struc into meaningful quadroco (D’Andrea & al. 2012)

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res with Flying Machines

ch & Institute for Dynamic H) F. Gramazio, M. Kohler and

ng elements used for the ctures, and translates them opter trajectories”

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Research Year: 2013-15 Research Project: Aerial Robot Thread Construction Research Team: AADRL Robert Stuart Smith Research Aims: “Fabricating in-situ a 3-dimensional weave of threads that is not achievable with conventional factory weaving machines” (Kokkugia, 2015)

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Research Year: 2015 Research Project: Building Tensile Structures with Flying Machines Research Team: Gramazio Kohler Research & Institute for Dynamic Systems and Control (ETH) F. Augugliaro, A. Mirjan, F. Gramazio, M. Kohler and R. D’Andrea Research Aims: “To autonomously realise load-bearing structures at full scale and proceeding a step further towards realworld scenarios.”

(D’andrea & al. 2015)

Pros No need to carry heavy loads Real-time on-site design and construction Free-formed geometry Autonomous navigation Swarm behavior Tensile elements

Pros No need to carry heavy loads Structural and practical outcome Fully made by the machines (the nodes, the weave and the tension are fully made by the machines)

age drones’ path inside a vironment) hitectural outcome

Cons Indoor (easier to manage drones’ path inside a laboratory controlled environment) At that stage no clear architectural outcome

Cons Indoor (easier to manage drones’ path inside a laboratory controlled environment)

ations nd cable beam structures

Possible future applications Drones weaving complex tensile structures

Possible future applications Drones weaving tensile and cable beam structures

oads

ents

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PART 2:

BUILDING WITH DRONES: EXPERIMENTS

4.0 UAV HARDWARE Up to now, research on drones used in building processes has been exclusively performed in laboratories.

Flying indoor is a safe environment, undisturbed by wind forces or any other uncertainty. The laboratories are usually equipped with motion sensitive cameras that allow the research teams to triangulate very precisely the position of the machines. This thesis intends to experiment flying robots in an outdoor environment to autonomously build a lightweight structure. These experiments are a further step towards real-world scenarios.

To enable these experiments, this thesis has been divided in 3 parts: the first is dedicated to find the right machine and the right processes to perform outdoor autonomous building. The second part tests the system accuracy and the third part focuses on experimenting the construction of outdoor lightweight structures.

4.1 Hovering flying machines Building an exterior structure calls for a hover-capable flying machine. Indeed, hover capable machines do not need constant motion to stay in place, ability that fixed wings aircrafts do not have. As stated by Raffaello D’Andrea “quadrocopters offer an excellent compromise between payload capabilities, agility, and robustness” (D’Andrea & al. 2013). Quadrotors therefore allow for vertical take off and landing (VTOL) and 6 axis of freedom (see flying principles’ scheme).

Historically the first successful flight of a quadrotors was in 1924, more than 10 years before the helicopters’ made in 1936. This difference is explained by the longer time it took engineers to develop the tail rotor to compensate the torque generated by the central propeller Finally, energetically speaking, quadrocopters are less energy efficient than fixed wings airplanes because of the constant motion of their rotors (Sturm, 2015).

4.2 Quadrotors’ requirements Choosing the appropriate drone to achieve outdoor autonomous building process is very similar to a craftsman choosing a tool. A drone is typically made of 4 main parts: the frame, the actuators (motors), the sensors and an embedded system. Here are the general requirements that the flying machines have to meet to achieve an outdoor building process: a. To be relatively small Building and weaving a lightweight structure calls for a machine small enough to fly through and around already built structures. The smaller the quadcopter is, the more agile it is. For this experiment a machine having a diameter between 30-50cm is ideal. b. To be relatively heavy As will be discussed later, the worst enemy of outdoor aerial construction is wind. A heavy flying machine stabilises the flight and minimises the machine’s displacement due to the exterior force. c. To be able to carry additional loads In order to weave a tensile structure, the quadrotors must carry the material that will be used for the construction process. Here: the rope, a roller and fixings. d. To be equipped with powerful positioning sensors See following chapter Due to the thesis’ time limitation, a commercial drone, the Phantom 3 advanced by DJI, was chosen. The Phantom 3 successfully meets all the above mentioned requirements and is considered to best of the best machines available on the market (theverge, 2015).

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4.1.3 Flying principles 1. To keep position: torques of all four rotors sum to zero 2. To keep position: thrust compensate earth gravity 3. To descend: equally decrease all rotors’ speed 4. To ascend: equally increase all rotors’ speed 5. To turn Left: increase rotors rotating clockwise 6. To turn right: increase rotors rotating counterclockwise 7. To move forward: increase speed of both back rotors 8. To move backward: increase speed of both front rotors p29

Figure 35a: Flying Machine Arena by the ETH

Figure 35b: Autonomous flight zones as developed by the ETH

Figure 36: PTAM mapping the edge points to measure its position

Figure 37: Ultrasonic and odometry sensors underneath the drone

Figure 38: GPS module integrated to the Phantom 3 p30

4.3 Positioning systems for autonomous flight The machines’ positioning system is the key to perform autonomous aerial construction. They allow the machine to compute its position and orientation in a relative space. In the actual drones’ research fields two different positioning strategies have been adopted: inboard and outboard positioning systems.

The Flying Machines Arena and the research groups based at the ETH typically uses outboard positioning systems. The laboratory is equipped with a set of motion capture cameras (see figure 34a) that triangulate the machines’ position in the laboratory’s referenced space. This information is sent to a computer, which runs the algorithms and sends the command to the to the flying machines (D’andrea & al., 2014) (see figure 34b). This strategy is typically designed for interior uses of drones. It is an excellent system for accurately calculating the machines’ position (+/-0.05m) and have as little hardware on the machines as possible.

Inboard positioning systems for drones are being developed by the Grasp Laboratory (University of Pennsylvania) and the Computer Vision Group (Technical University of Munich) amongst others. This strategy implies for the machine to carry on board a set of sensors that will allow the machine to compute its position. 1 The most commonly used technique is the visual odometry, or PTAM (Parallel Tracking and Mapping) which allows the robot to determine its orientation and position by analysing its on board cameras’ images. The machine recognises a set of “edge points” (see figure 35) and triangulate its position according to them. This system can be used out of laboratories however it has some limitations due to the camera’s vision range: beyond 5 meters, the machine looses the ability to detect the edge points and is unable to calculate its position anymore (Sturm, 2015).

The positioning system adapted to an outdoor autonomous navigation is mainly a set of inboard strategies. To calculate its position the selected machine, the Phantom 3, is equipped with both a GPS and GLONASS2 modules (see figure 37) that geolocalises the machine according to its relative position to the satellites. The machine is also equipped with a visual odometer and ultrasonic sensors facing the ground to calculated its altitude and position (see figure 38). All these informations and the other sensors data from the gyroscope, the accelerometer and magnetometer are analysed by the main controller. This mix of sensors give a rather accurate position of the machine and are the first step towards outdoor autonomous building process.

1 Typically the machines will be equipped with a gyroscope (to measure an maintain orientation), an accelerometer (to measure acceleration and ensure flight stability), a magnetometer (to measure the direction of the magnetic field).

2 The GLONASS system is the Russian equivalent to GPS. Both systems are the most accurate geo-referencing platforms worldwide.

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4.4 Machine customisation Drones, like any computer-controlled machine, can be programmed in their movements.

They are able to access any point in space but are general multi-purpose machines and need to be customised for a specific architectural application. Each task demands a different set of tools. This thesis aims to build a tensile structure using rope, therefore the flying robot is equipped with a passive roller to dispense the rope as the machine is flying through space. A set of propeller guards as much as a safety wire are installed to prevent the rope to get stuck in the propellers.

Figure 38: DJI Phantom 3 Advanced

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A. Propellers guards The propellers guards are preventing damages on the machine when building a 3 dimensional tensile structure. The angle between roller dispensing the thread and the woven structure can result in the thread getting stuck in the machine’s propellers and provoke the crash of the machine. To avoid this from happening, the propellers are protected horizontally with a circular frame.

B. Safety wire A safety wire is placed around and between the propellers guards. It has two purposes: the first one is to reinforce the stability of the propellers guards and the second is to prevent the unrolled thread to get stuck between the propellers.

C. Passive Roller A passive roller is installed at the back of the machine below the propellers. It is made of a 3d printed U frame fixed above the camera gimbal on the machine’s gravity center. In doing so, the additional weight of the system doesn’t disturb the flying machine’s equilibrium. The roller’s friction is adjustable so it respond to the right torque to unroll the thread and build the structures.

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5.0 SOFTWARE: ENABLING AUTONOMOUS BUILDING PROCESS In order to achieve an outdoor autonomous building process, the drones must be capable of autonomous flight. As part of the digital fabrication field, the strategies available to the designers are fully computer based. The Utopian vision behind automated building processes is freeing the building sites from human intervention.

To do so, humans must equip the machines with a kind of intelligence that makes them autonomous. Therefore human intervention in building processes shifts in time and place: a. through code, they plan the machines actions prior to the on site intervention and b. they are occupying an off site position, monitoring the machines’ actions.

5.1 Strategies to achieve autonomous building process: Various strategies are available to engineers to program autonomous building processes. For this thesis a process based on predefined gps based trajectories was adopted. The system is developed such as the quadrotors autonomously follow given trajectories. These latest are drawn in a CAD environment and defined by a set of points placed in a geo-referenced space (latitute and longitude). The 3rd dimension is defined by the position of the machine relative to the ground. This strategy was adopted for its compatibility with an outdoor flying machines equipped with a GPS and GLONASS modules. The Phantom 3 is capable of computing its position in space and giving it points to follow referenced in the same space makes it understandable by the machine.

This process is exclusively digitally and remotely programmed. Unlike actual construction methods, human intervention is secluded to an off site position and the on site building process is exclusively performed by the flying robots. The building information is digitally transmitted to the machine via automatic Hertz frequencies (See diagram on the right).

In order to build the desired structure, the strategy is based on reverse engineering methods: the desired outcomes are first set, to be then translated into elements understandable by the flying robots. Here is the breaking down of the components:

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Off Site Human Intervention

Telemetry

Analysis

Parametric Design

Parametric Building Instructions

Tasks Commands

Flow of data

Wireless Transmission (via Hertz)

Drones’ Charging Station

On Site Autonomous Aerial Robotic Intervention

Flow of data

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first parametrically design the final result (1), then translate the architectural outcome into quadcopter trajectories (2), break these trajectories into waypoints (3), translate those waypoints into GPS coordinates and height (4) and transmit them to the machine to be executed (5).

5.2 The Design of the robotic process As part of a cross-disciplinary approach to architecture, this thesis is looking into field such as mechatronics, engineering and computer sciences. Being a computer-controlled machine, drones can be programmed in their movements to achieve an architectural outcome. However, as stated in “Integrating robotic fabrication in design�: the production of control data in the form of coded instructions require programming skills as well as an understanding of robotics concepts such as kinematics, which lie outside most architects’ domain of expertise (Budig & al. 2012).

With the development of digital tools such as GrasshopperTM, the process developed for this thesis allows for making flying robots intuitively controlled by architects. The design and the resulting trajectories are drawn in GrasshopperTM which visual interface is well suited for quick prototyping and simulations. Once the simulation is done, the trajectories are exported to the flying robots through an interface called FlyLitchiTM. The latest is a software developed by a third party built from the DJI Phantom 3 Software Development Kit (SDK). Through the interface of an app, the software acts as a high controller and remotely transmit the autonomous flight procedures to the machine.

Commercially developed, FlyLitchiTM is an user friendly platform performing very well.

However being developed for aerial filming purposes the software lacks of some precision mainly in the height measurement as it only records and accepts round numbers in meters.

5.3 Data conversion: Between XYZ and geographic coordinates The design process developed for thesis is based on CAD softwares, namely Rhino3DTM and GrasshopperTM. These are digital space with units being either based on a metric or an imperial system. However as stated earlier, the autonomous building process developed for this thesis relies on a different spatial system; the geo-referenced points.

This implies that the trajectories points need to be translated into the referencing system understood by the flying robot. The parametric data drawn in an XYZ space are translated using gHowlTM a GrasshopperTM plug-in. An XYZ (2m,2m,2m) point becomes latitude, longitude and height (-37.842929783207246o, 144.9805671349167o, 3m).

This process also works backwards allowing to analyse the data recorded by the flying robot while autonomously flying (see figure 39).

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Sequence: Showing a pre flight simulation

Grasshopper Definition: Showing the data conversion from XYZ to gps coordinates & vice versa

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5.4 Tool ecology: Input and extract data The selected digital tools are enabling drones to perform an outdoor autonomous building process. An architectural outcome is first translated to trajectories understandable by the flying robot and this information is sent to the machine. Once the flying procedures received, the drone flies autonomously and records 10 times/sec a set of data including, height, position and velocity. This data can be then extracted and analysed to highlight eventual discrepancies between what is digitally planned and what happens in real space. The digital blueprint sent to the machine and the extracted data can be both read in Rhino3dTM and GrasshopperTM environment. Having them on the same canvas facilitate the result’s analysis.

Tool: Rhino 3d, Grasshopper Use: Draw geometries and flight paths in an xyz domain

Tool: GHowl (grasshopper plugin) Use: Convert flight paths’ xyz points into geographic coordinates and relative height to the ground

Tool: Litchi Use: import georeferenced trajectories and transmit the mission to the machines

Feedback loop: The extract to optimise the following tra

Plan Autonomous Trajectories

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Tool: Flight replay or Healthy drones Use: Turn log files into readable results

Tool: Excel Use: Read the recorded flight logs

ted data are used ajectories

Outdoor Aerial Building Process

Tool: Rhino, Grasshopper, GHowl Use: flight paths

Extract and Analyse data Figure 39: Digital tools’ scheme p39

latitude longitude altitude(feet)ascent(feet) speed(mph) distance(feet)max_altitude(feet) max_ascent(feet) max_speed(mph) max_distance(feet) time(millisecond) datetime(utc)datetime(local) satellites pressure(Pa) temperature(F) voltage(v) home_latit -37.842888144.980546 144.980592 49:09.2 49:09.2 -37.84288 -37.842908 17 0 17 0 4.2 0 15 0 23 0 23 0 4.48 0 15 0 22049 0 49:31.2 49:31.2 1414 00 00 15.720-37.842889 -37.842888144.980544 144.980592 260 49:09.4 49:09.4 -37.84288 -37.842909 17 0 17 0 4.2 0 15 0 23 0 23 0 4.48 0 15 0 22149 49:31.3 49:31.3 1414 00 00 15.720-37.842889 -37.842888 144.980592 0 0 0 0 0 0 0 0 385 49:09.6 49:09.6 14 0 0 20 -37.84288 -37.842909 144.980542 17 17 4.2 16 23 23 4.48 16 22247 49:31.4 49:31.4 14 0 0 15.7 -37.842889 -37.842888144.980542 144.980592 643 49:09.8 49:09.8 -37.84288 -37.842909 17 0 17 0 4.2 0 16 0 23 0 23 0 4.48 0 16 0 22334 49:31.5 49:31.5 1414 00 00 15.720-37.842889 -37.842888144.980541 144.980592 830 49:10.0 49:10.0 -37.84288 -37.84291 16 0 16 0 4.2 0 16 0 23 0 23 0 4.48 0 16 0 22448 49:31.6 49:31.6 1314 00 00 15.720-37.842889 -37.842888144.980537 144.980592 898 49:10.1 49:10.1 -37.84288 -37.842912 16 0 16 0 4.38 0 18 0 23 0 23 0 4.48 0 18 0 22656 49:31.8 49:31.8 1314 00 00 15.720-37.842889 -37.842888144.980533 144.980591 977 49:10.1 49:10.1 -37.84288 -37.842913 15 0 15 0 4.38 0 19 0 23 0 23 0 4.48 0 19 0 22970 49:32.1 49:32.2 1314 00 00 15.720-37.842889 -37.842888 144.980591 0 0 0 0 0 0 0 0 1081 49:10.2 49:10.2 14 0 0 20 -37.84288 -37.842916 144.980526 14 14 4.2 21 23 23 4.48 21 23177 49:32.3 49:32.3 13 0 0 15.7 -37.842889 -37.842888144.980524 144.980591 1179 49:10.3 49:10.3 -37.84288 -37.842917 14 0 14 0 4.2 0 22 0 23 0 23 0 4.48 0 22 0 23268 49:32.4 49:32.4 1314 00 00 15.720-37.842889 -37.842888144.980522 144.980591 1277 49:10.4 49:10.4 -37.84288 -37.842918 14 0 14 0 4.2 0 22 0 23 0 23 0 4.48 0 22 0 23362 49:32.5 49:32.5 1314 00 00 15.720-37.842889 -37.842888 144.98052 144.980591 1374 49:10.5 49:10.5 -37.84288 -37.842918 13 0 13 0 4.2 0 23 0 23 0 23 0 4.48 0 23 0 23460 49:32.6 49:32.6 1314 00 00 15.720-37.842889 -37.842888144.980519 144.980591 1506 49:10.7 49:10.7 -37.84288 -37.842919 13 0 13 0 4.2 0 23 0 23 0 23 0 4.48 0 23 0 23562 49:32.7 49:32.7 1314 00 00 15.720-37.842889 -37.842888 144.980591 0 0 0 0 0 0 0 0 1601 49:10.8 49:10.8 14 0 0 20 -37.84288 -37.842919 144.980519 13 13 4.2 23 23 23 4.48 23 23647 49:32.8 49:32.8 13 0 0 15.7 -37.842889 -37.842888144.980515 144.980591 1733 49:10.9 49:10.9 -37.84288 -37.842921 13 0 13 0 4.11 0 25 0 23 0 23 0 4.48 0 25 0 23877 49:33.0 49:33.0 1414 00 00 15.720-37.842889 -37.842888144.980514 144.980591 1956 49:11.1 49:11.1 -37.84288 -37.842922 12 0 12 0 4.2 0 25 0 23 0 23 0 4.48 0 25 0 23989 49:33.2 49:33.2 1414 00 00 15.720-37.842889 -37.842888 144.98051 144.980591 0.67 0.67 2211 49:11.4 49:11.4 -37.84288 -37.842923 12 0 12 0 4.2 26 0 23 0 23 0 4.48 26 0 24073 49:33.2 49:33.2 1314 00 00 15.720-37.842889 -37.842888144.980508 144.980591 0.89 0.89 2293 49:11.5 49:11.5 -37.84288 -37.842924 11 0 11 0 4.38 27 0 23 0 23 0 4.48 27 0 24256 49:33.4 49:33.4 1414 00 00 15.720-37.842889 -37.842888 144.980591 0 0 0.89 0 0 0 0.89 0 2505 49:11.7 49:11.7 14 0 0 20 -37.84288 -37.842924 144.980508 11 11 4.38 27 23 23 4.48 27 24291 49:33.5 49:33.5 14 0 0 15.7 -37.842889 -37.842888144.980504 144.980591 1.12 1.12 2578 49:11.7 49:11.7 -37.84288 -37.842925 11 1 11 1 4.38 28 0 23 1 23 1 4.48 28 0 24413 49:33.6 49:33.6 1414 00 00 15.720-37.842889 -37.842888 144.980591 1.12 1.12 2673 49:11.8 49:11.8 -37.84288 -37.842927 144.9805 10 1 10 1 4.38 29 0 23 1 23 1 4.48 29 0 24549 49:33.7 49:33.9 1314 00 00 15.720-37.842889 -37.842888144.980497 144.980591 1.12 1.12 2783 49:11.9 49:11.9 -37.84288 -37.842928 10 1 10 1 4.3 31 0 23 1 23 1 4.48 31 0 24836 49:34.0 49:34.0 1212 00 00 15.720-37.842889 -37.842888144.980495 144.980591 1.34 1.34 2871 49:12.0 49:12.0 -37.84288 -37.842929 91 91 4.11 31 0 23 1 23 1 4.48 31 0 24881 49:34.0 49:34.0 1212 00 00 15.720-37.842889 -37.842888 144.980591 2 2 1.12 0 2 2 1.34 0 3000 49:12.2 49:12.2 13 0 0 20 -37.84288 -37.84293 144.980493 9 9 4.11 32 23 23 4.48 32 24973 49:34.1 49:34.1 14 0 0 15.7 -37.842889 -37.842888 144.980591 2 2 0.89 0 2 2 1.34 0 3215 49:12.4 49:12.4 13 0 0 20 -37.84288 -37.842931 144.980491 9 9 4.11 32 23 23 4.48 32 25074 49:34.2 49:34.2 14 0 0 15.7 -37.842889 -37.842887 144.98049 144.98059 0.89 1.34 3331 49:12.5 49:12.5 -37.84288 -37.842931 82 82 4.21 33 0 23 2 23 2 4.48 33 0 25186 49:34.3 49:34.3 1214 00 00 15.720-37.842889 -37.842887144.980488 144.98059 0.89 1.34 3494 49:12.7 49:12.7 -37.84288 -37.842932 82 82 4.21 34 0 23 2 23 2 4.48 34 0 25273 49:34.4 49:34.4 1214 00 00 15.720-37.842889 -37.842887144.980486 144.98059 0.89 1.34 3605 49:12.8 49:12.8 -37.84288 -37.842933 82 82 4.21 34 0 23 2 23 2 4.48 34 0 25453 49:34.6 49:34.6 1214 00 00 15.720-37.842889 -37.842887 144.98059 2 2 0.67 0 2 2 1.34 0 3679 49:12.8 49:12.9 14 0 0 20 -37.84288 -37.842934 144.980484 7 7 4.21 35 23 23 4.48 35 25540 49:34.7 49:34.7 12 0 0 15.7 -37.842889 -37.842887 144.98059 3 3 0.22 0 3 3 1.34 0 3773 49:12.9 49:12.9 15 0 0 20 -37.84288 -37.842935 144.980482 7 7 4.3 35 23 23 4.48 35 25634 49:34.8 49:34.8 12 0 0 15.7 -37.842889 -37.842887 144.98048 144.98059 0.22 1.34 4173 49:13.3 49:13.3 -37.84288 -37.842935 73 73 4.3 36 0 23 3 23 3 4.48 36 0 25732 49:34.9 49:34.9 1213 00 00 15.720-37.842889 -37.842887144.980479 144.98059 1.34 4219 49:13.4 49:13.4 -37.84288 -37.842936 63 63 4.38 0 37 0 23 3 23 3 4.48 37 0 25900 49:35.1 49:35.1 1213 00 00 11.420-37.842889 -37.842887144.980477 144.98059 1.34 4347 49:13.5 49:13.5 -37.84288 -37.842937 63 63 4.39 0 37 0 23 3 23 3 4.48 37 0 26023 49:35.2 49:35.2 1213 00 00 11.420-37.842889 -37.842887144.980475 144.98059 1.34 4410 49:13.6 49:13.6 -37.84288 -37.842938 63 63 4.3 0 38 0 23 3 23 3 4.48 38 0 26244 49:35.4 49:35.5 1214 00 00 11.420-37.842889 -37.842887 144.98059 3 3 0 0 3 3 1.34 0 4504 49:13.7 49:13.7 14 0 0 20 -37.84288 -37.84294 144.980468 5 5 2.76 40 23 23 4.48 40 26437 49:35.6 49:35.6 11 0 0 11.4 -37.842889 -37.842887144.980467 144.98059 1.34 4590 49:13.8 49:13.8 -37.84288 -37.842941 53 53 2.21 0 40 0 23 3 23 3 4.48 40 0 26617 49:35.8 49:35.8 1114 00 00 11.420-37.842889 -37.842887144.980467 144.98059 1.34 4868 49:14.0 49:14.0 -37.84288 -37.842941 53 53 0.81 0 40 0 23 3 23 3 4.48 40 0 26664 49:35.8 49:35.8 1114 00 00 11.420-37.842889 -37.842887144.980468 144.98059 1.34 4946 49:14.1 49:14.1 -37.84288 -37.842941 53 53 0.45 0 40 0 23 3 23 3 4.48 40 0 26746 49:35.9 49:35.9 1214 00 00 11.420-37.842889 -37.842887144.980468 144.98059 1.34 5009 49:14.2 49:14.2 -37.84288 -37.84294 53 53 0.5 0 40 0 23 3 23 3 4.48 40 0 26846 49:36.0 49:36.0 1214 00 00 11.420-37.842889 -37.842887 144.98059 3 3 0 0 3 3 1.34 0 5113 49:14.3 49:14.3 14 0 0 20 -37.84288 -37.84294 144.980468 5 5 0.71 40 23 23 4.48 40 26947 49:36.1 49:36.1 12 0 0 11.4 -37.842889 -37.842887144.980467 144.98059 1.34 5270 49:14.4 49:14.4 -37.84288 -37.84294 53 53 0.71 0 40 0 23 3 23 3 4.48 40 0 27051 49:36.2 49:36.2 1214 00 00 11.420-37.842889 -37.842887144.980467 144.98059 1.34 5424 49:14.6 49:14.6 -37.84288 -37.84294 53 53 0.92 0 40 0 23 3 23 3 4.48 40 0 27285 49:36.4 49:36.4 1314 00 00 11.420-37.842889 -37.842887144.980466 144.98059 1.34 5490 49:14.7 49:14.7 -37.84288 -37.84294 53 53 0.92 0 40 0 23 3 23 3 4.48 40 0 27358 49:36.5 49:36.5 1314 00 00 11.420-37.842889 -37.842887144.980466 144.98059 1.34 5572 49:14.7 49:14.7 -37.84288 -37.84294 53 53 0.67 0 40 0 23 3 23 3 4.48 40 0 27473 49:36.6 49:36.6 1414 00 00 11.420-37.842889 -37.842887 144.98059 3 3 0 0 3 3 1.34 0 5695 49:14.9 49:14.9 14 0 0 20 -37.84288 -37.84294 144.980465 5 5 0.67 41 23 23 4.48 41 27611 49:36.8 49:36.8 13 0 0 11.4 -37.842889 -37.842887144.980464 144.98059 1.34 5796 49:15.0 49:15.0 -37.84288 -37.84294 53 53 0.45 0 41 0 23 3 23 3 4.48 41 0 27740 49:36.9 49:36.9 1314 00 00 11.420-37.842889 -37.842887144.980464 144.98059 0.22 1.34 6040 49:15.2 49:15.2 -37.84288 -37.84294 53 53 0.22 41 0 23 3 23 3 4.48 41 0 27827 49:37.0 49:37.0 1314 00 00 11.420-37.842889 -37.842887144.980464 144.98059 1.34 6083 49:15.2 49:15.2 -37.84288 -37.84294 53 53 0.22 0 41 0 23 3 23 3 4.48 41 0 27916 49:37.1 49:37.1 1314 00 00 11.420-37.842889 -37.842887144.980465 144.98059 1.34 6176 49:15.3 49:15.3 -37.84288 -37.84294 53 53 0.22 0 41 0 23 3 23 3 4.48 41 0 28087 49:37.3 49:37.3 1214 00 00 11.420-37.842889 -37.842887 144.98059 3 3 0 0 3 3 1.34 0 6271 49:15.4 49:15.4 14 0 0 20 -37.84288 -37.842939 144.980465 5 5 0.32 41 23 23 4.48 41 28235 49:37.4 49:37.4 12 0 0 11.4 -37.842889 -37.842887144.980465 144.98059 1.34 6433 49:15.6 49:15.7 15.7-37.842889 -37.84288 -37.842939 53 53 0.32 0 40 0 23 3 23 3 4.48 41 0 28351 49:37.5 49:37.5 1214 00 00 11.4 -37.842887144.980466 144.98059 1.34 6522 49:15.7 49:15.7 15.7-37.842889 -37.84288 -37.842939 53 53 0.5 0 40 0 23 3 23 3 4.48 41 0 28437 49:37.6 49:37.6 1214 00 00 11.4 -37.842887144.980466 144.98059 1.34 6646 49:15.8 49:15.8 15.7-37.842889 -37.84288 -37.842938 53 53 0.92 0 40 0 23 3 23 3 4.48 41 0 28538 49:37.7 49:37.7 1115 00 00 11.4 -37.842887144.980467 144.98059 1.34 6723 49:15.9 49:15.9 15.7-37.842889 -37.84288 -37.842938 53 53 1.2 0 40 0 23 3 23 3 4.48 41 0 28638 49:37.8 49:37.8 1115 00 00 11.4 -37.842887 144.98059 3 3 0 0 3 3 1.34 0 6846 49:16.0 49:16.1 15 0 0 15.7 -37.84288 -37.842938 144.980467 5 5 1.2 40 23 23 4.48 41 28732 49:37.9 49:37.9 11 0 0 11.4 -37.842889 -37.842887144.980467 144.98059 1.34 6943 49:16.1 49:16.1 15.7-37.842889 -37.84288 -37.842937 53 53 1.86 0 40 0 23 3 23 3 4.48 41 0 28964 49:38.1 49:38.1 1115 00 00 11.4 -37.842887144.980467 144.98059 1.34 7170 49:16.3 49:16.4 15.7-37.842889 -37.84288 -37.842934 53 53 2.93 0 39 0 23 3 23 3 4.48 41 0 29010 49:38.2 49:38.2 1115 00 00 11.4 -37.842887144.980467 144.98059 1.34 7411 49:16.6 49:16.6 15.7-37.842889 -37.84288 -37.842933 53 53 3.37 0 39 0 23 3 23 3 4.48 41 0 29097 49:38.3 49:38.3 1115 00 00 11.4 -37.842887144.980467 144.98059 1.34 7638 49:16.8 49:16.8 15.7-37.842889 -37.84288 -37.842931 53 53 3.82 0 39 0 23 3 23 3 4.48 41 0 29215 49:38.4 49:38.4 1115 00 00 11.4 -37.842929 144.980467 5 5 4.04 38 23 23 4.48 41 29385 49:38.6 49:38.6 11 0 0 11.4 -37.842889 -37.842908 144.980546 17 17 4.2 15 23 23 4.48 15 22049 49:31.2 49:31.2 14 0 0 15.7 -37.842889 -37.842909 144.980544 17 17 4.2 15 23 23 4.48 15 22149 49:31.3 49:31.3 14 0 0 15.7 -37.842889 -37.842909 144.980542 17 17 4.2 16 23 23 4.48 16 22247 49:31.4 49:31.4 14 0 0 15.7 -37.842889 -37.842909 144.980542 17 17 4.2 16 23 23 4.48 16 22334 49:31.5 49:31.5 14 0 0 15.7 -37.842889 -37.84291 144.980541 16 16 4.2 16 23 23 4.48 16 22448 49:31.6 49:31.6 13 0 0 15.7 -37.842889 -37.842912 144.980537 16 16 4.38 18 23 23 4.48 18 22656 49:31.8 49:31.8 13 0 0 15.7 -37.842889 -37.842913 144.980533 15 15 4.38 19 23 23 4.48 19 22970 49:32.1 49:32.2 13 0 0 15.7 -37.842889 -37.842916 144.980526 14 14 4.2 21 23 23 4.48 21 23177 49:32.3 49:32.3 13 0 0 15.7 -37.842889 -37.842917 144.980524 14 14 4.2 22 23 23 4.48 22 23268 49:32.4 49:32.4 13 0 0 15.7 -37.842889 -37.842918 144.980522 14 14 4.2 22 23 23 4.48 22 23362 49:32.5 49:32.5 13 0 0 15.7 -37.842889 -37.842918 144.98052 13 13 4.2 23 23 23 4.48 23 23460 49:32.6 49:32.6 13 0 0 15.7 -37.842889 -37.842919 144.980519 13 13 4.2 23 23 23 4.48 23 23562 49:32.7 49:32.7 13 0 0 15.7 -37.842889 -37.842919 144.980519 13 13 4.2 23 23 23 4.48 23 23647 49:32.8 49:32.8 13 0 0 15.7 -37.842889 -37.842921 144.980515 13 13 4.11 25 23 23 4.48 25 23877 49:33.0 49:33.0 14 0 0 15.7 -37.842889 -37.842922 144.980514 12 12 4.2 25 23 23 4.48 25 23989 49:33.2 49:33.2 14 0 0 15.7 -37.842889 -37.842923 144.98051 12 12 4.2 26 23 23 4.48 26 24073 49:33.2 49:33.2 13 0 0 15.7 -37.842889 -37.842924 144.980508 11 11 4.38 27 23 23 4.48 27 24256 49:33.4 49:33.4 14 0 0 15.7 -37.842889 -37.842924 144.980508 11 11 4.38 27 23 23 4.48 27 24291 49:33.5 49:33.5 14 0 0 15.7 -37.842889 -37.842925 144.980504 11 11 4.38 28 23 23 4.48 28 24413 49:33.6 49:33.6 14 0 0 15.7 -37.842889 -37.842927 144.9805 10 10 4.38 29 23 23 4.48 29 24549 49:33.7 49:33.9 13 0 0 15.7 -37.842889 -37.842928 144.980497 10 10 4.3 31 23 23 4.48 31 24836 49:34.0 49:34.0 12 0 0 15.7 -37.842889 -37.842929 144.980495 9 9 4.11 31 23 23 4.48 31 24881 49:34.0 49:34.0 12 0 0 15.7 -37.842889 -37.84293 144.980493 9 9 4.11 32 23 23 4.48 32 24973 49:34.1 49:34.1 14 0 0 15.7 -37.842889 -37.842931 144.980491 9 9 4.11 32 23 23 4.48 32 25074 49:34.2 49:34.2 14 0 0 15.7 -37.842889 -37.842931 144.98049 8 8 4.21 33 23 23 4.48 33 25186 49:34.3 49:34.3 12 0 0 15.7 -37.842889 -37.842932 144.980488 8 8 4.21 34 23 23 4.48 34 25273 49:34.4 49:34.4 12 0 0 15.7 -37.842889 -37.842933 144.980486 8 8 4.21 34 23 23 4.48 34 25453 49:34.6 49:34.6 12 0 0 15.7 -37.842889 -37.842934 144.980484 7 7 4.21 35 23 23 4.48 35 25540 49:34.7 49:34.7 12 0 0 15.7 -37.842889 -37.842935 144.980482 7 7 4.3 35 23 23 4.48 35 25634 49:34.8 49:34.8 12 0 0 15.7 -37.842889 -37.842935 144.98048 7 7 4.3 36 23 23 4.48 36 25732 49:34.9 49:34.9 12 0 0 15.7 -37.842889 -37.842936 144.980479 6 6 4.38 37 23 23 4.48 37 25900 49:35.1 49:35.1 12 0 0 11.4 -37.842889 -37.842937 144.980477 6 6 4.39 37 23 23 4.48 37 26023 49:35.2 49:35.2 12 0 0 11.4 -37.842889 -37.842938 144.980475 6 6 4.3 38 23 23 4.48 38 26244 49:35.4 49:35.5 12 0 0 11.4 -37.842889 -37.84294 144.980468 5 5 2.76 40 23 23 4.48 40 26437 49:35.6 49:35.6 11 0 0 11.4 -37.842889 -37.842941 144.980467 5 5 2.21 40 23 23 4.48 40 26617 49:35.8 49:35.8 11 0 0 11.4 -37.842889 -37.842941 144.980467 5 5 0.81 40 23 23 4.48 40 26664 49:35.8 49:35.8 11 0 0 11.4 -37.842889 -37.842941 144.980468 5 5 0.45 40 23 23 4.48 40 26746 49:35.9 49:35.9 12 0 0 11.4 -37.842889 -37.84294 144.980468 5 5 0.5 40 23 23 4.48 40 26846 49:36.0 49:36.0 12 0 0 11.4 -37.842889 -37.84294 144.980468 5 5 0.71 40 23 23 4.48 40 26947 49:36.1 49:36.1 12 0 0 11.4 -37.842889 -37.84294 144.980467 5 5 0.71 40 23 23 4.48 40 27051 49:36.2 49:36.2 12 0 0 11.4 -37.842889 -37.84294 144.980467 5 5 0.92 40 23 23 4.48 40 27285 49:36.4 49:36.4 13 0 0 11.4 -37.842889 -37.84294 144.980466 5 5 0.92 40 23 23 4.48 40 27358 49:36.5 49:36.5 13 0 0 11.4 -37.842889 -37.84294 144.980466 5 5 0.67 40 23 23 4.48 40 27473 49:36.6 49:36.6 14 0 0 11.4 -37.842889 -37.84294 144.980465 5 5 0.67 41 23 23 4.48 41 27611 49:36.8 49:36.8 13 0 0 11.4 -37.842889 -37.84294 144.980464 5 5 0.45 41 23 23 4.48 41 27740 49:36.9 49:36.9 13 0 0 11.4 -37.842889 -37.84294 144.980464 5 5 0.22 41 23 23 4.48 41 27827 49:37.0 49:37.0 13 0 0 11.4 -37.842889 -37.84294 144.980464 5 5 0.22 41 23 23 4.48 41 27916 49:37.1 49:37.1 13 0 0 11.4 -37.842889 -37.84294 144.980465 5 5 0.22 41 23 23 4.48 41 28087 49:37.3 49:37.3 12 0 0 11.4 -37.842889 p40 -37.842939 144.980465 5 5 0.32 41 23 23 4.48 41 28235 49:37.4 49:37.4 12 0 0 11.4 -37.842889 -37.842939 144.980465 5 5 0.32 40 23 23 4.48 41 28351 49:37.5 49:37.5 12 0 0 11.4 -37.842889 -37.842939 144.980466 5 5 0.5 40 23 23 4.48 41 28437 49:37.6 49:37.6 12 0 0 11.4 -37.842889

tude home_longitude velocityX(mph) velocityY(mph) velocityZ(mph)pitch(deg) 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 0 0 -1.79 -3.36 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.58 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.58 0 1.79 0 -1 89144.980592 144.980592 0 0 -1.79 -3.36 1.79 0 -1 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -1 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.57 0 -2 89144.980592 144.980592 -1.79 0 -3.36 0 1.79 0 89144.980592 144.980592 -0.67 -3 -1.79 0 -3.36 0 1.79 89144.980592 144.980592 -0.89 -2 -1.79 0 -3.58 0 1.79 89144.980592 144.980592 -0.89 -2 -1.79 0 -3.58 0 1.79 89144.980592 144.980592 -1.12 -2 -1.79 0 -3.58 0 1.79 89144.980592 144.980592 -1.12 -2 -1.79 0 -3.58 0 1.79 89144.980592 144.980592 -1.12 -2 -1.79 0 -3.58 0 1.57 89144.980592 144.980592 -1.34 -2 -1.79 0 -3.36 0 1.57 89144.980592 144.980592 0 0 -1.12 -2 -1.79 -3.36 1.57 89144.980592 144.980592 -0.89 -2 -1.79 0 -3.36 0 1.57 89144.980592 144.980592 -0.89 -2 -2.01 0 -3.36 0 1.57 89144.980592 144.980592 -0.89 -2 -2.01 0 -3.36 0 1.57 89144.980592 144.980592 -0.89 -2 -2.01 0 -3.36 0 1.57 89144.980592 144.980592 0 0 -0.67 -2 -2.01 -3.36 1.57 89144.980592 144.980592 0 0 -0.22 -2 -2.01 -3.36 1.79 89144.980592 144.980592 -0.22 -2 -2.01 0 -3.36 0 1.79 89144.980592 144.980592 -1.79 0 -3.58 0 1.79 0 -2 89144.980592 144.980592 -2.01 0 -3.58 0 1.57 0 -2 89144.980592 144.980592 -1.79 0 -3.58 0 1.57 0 -2 89144.980592 144.980592 0 0 -1.34 -2.24 0.89 0 -2 89144.980592 144.980592 -1.12 0 -1.79 0 0.67 0 13 89144.980592 144.980592 -0.45 0 -0.67 0 0 0 15 89144.980592 144.980592 00 -0.45 0 00 4 89144.980592 144.980592 -0.22 0 -0.45 0 0 0 -1 89144.980592 144.980592 0 0 -0.22 -0.67 0 0 -1 89144.980592 144.980592 -0.22 0 -0.67 0 0 0 -1 89144.980592 144.980592 -0.22 0 -0.89 0 00 0 89144.980592 144.980592 -0.22 0 -0.89 0 00 0 89144.980592 144.980592 00 -0.67 0 00 1 89144.980592 144.980592 0 0 0 -0.67 00 1 89144.980592 144.980592 00 -0.45 0 00 1 89144.980592 144.980592 0.22 00 -0.22 0 0 1 89144.980592 144.980592 00 -0.22 0 00 1 89144.980592 144.980592 0.22 0 00 00 1 89144.980592 144.980592 0.22 0 0.22 0 00 0 89144.980592 144.980592 0.22 0 0.22 0 00 1 89144.980592 144.980592 0.45 0 0.22 0 00 1 89144.980592 144.980592 0.89 0 0.22 0 00 89144.980592 144.980592 1.12 0 0.45 0 0 0 -3 89144.980592 144.980592 1.12 0 0.45 0 0 0 -7 89144.980592 144.980592 1.79 0 0.45 0 -0.22 0 -10 89144.980592 144.980592 2.91 0 0.22 0 -0.22 0 -10 89144.980592 144.980592 3.36 0 0.22 0 -0.22 0 -12 89144.980592 144.980592 3.8 0 0.22 0 -0.22 0 -12 144.980592 4.03 0.22 -0.22 -11 144.980592 -1.79 -3.36 1.79 -10 -2 -8 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -1.79 -3.58 1.79 -1 144.980592 -1.79 -3.36 1.79 -1 144.980592 -1.79 -3.36 1.79 -1 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.36 1.57 -2 144.980592 -1.79 -3.36 1.79 -3 144.980592 -1.79 -3.36 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -1.79 -3.58 1.57 -2 144.980592 -1.79 -3.36 1.57 -2 144.980592 -1.79 -3.36 1.57 -2 144.980592 -1.79 -3.36 1.57 -2 144.980592 -2.01 -3.36 1.57 -2 144.980592 -2.01 -3.36 1.57 -2 144.980592 -2.01 -3.36 1.57 -2 144.980592 -2.01 -3.36 1.57 -2 144.980592 -2.01 -3.36 1.79 -2 144.980592 -2.01 -3.36 1.79 -2 144.980592 -1.79 -3.58 1.79 -2 144.980592 -2.01 -3.58 1.57 -2 144.980592 -1.79 -3.58 1.57 -2 144.980592 -1.34 -2.24 0.89 144.980592 -1.12 -1.79 0.67 13 144.980592 -0.45 -0.67 0 15 4 144.980592 0 -0.45 0 144.980592 -0.22 -0.45 0 -1 144.980592 -0.22 -0.67 0 -1 144.980592 -0.22 -0.67 0 -1 144.980592 -0.22 -0.89 0 0 144.980592 -0.22 -0.89 0 0 144.980592 0 -0.67 0 1 144.980592 0 -0.67 0 1 144.980592 0 -0.45 0 1 144.980592 0 -0.22 0 1 144.980592 0 -0.22 0 1 144.980592 0.22 0 0 1 144.980592 0.22 0.22 0 0 144.980592 0.22 0.22 0 1 144.980592 0.45 0.22 0 1

roll(deg) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1

0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 0 0 0 1 0 -1 -1 0 0 0 1 3 4 4 4 4 4 2 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 0 0 0 1 0 -1 -1 0 0 0 1 3 4 4 4 4 4 2 1

yaw(deg) 0-113 0-113 0 -113 0 -113 0 -113 0 -113 0 -113 0 -113 0 -113 0 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 0-113 1-113 1-113 1-113 0-113 0-113 0-113 0-113 1-113 1-113 1-113 1-113 1-113 1-110 0-102 0 -93 0 -85 0 -76 0 -66 1 -57 1 -39 1 -30 1 -21 0 -13 0 1 -7 1 -3 1 0 1 1 1 2 1 2 1 3 1 3 1 3 0 3 3 3 -113 3 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -113 -110 -102 -93 -85 -76 -66 -57 -39 -30 -21 -13 -7 -3 0 1

26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 27 27 27 27 27 26 26 26 26 26 26 26

powerlevel isflying 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 15 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 20 11 1 15 11 1 15 11 1 15 11 1 15 11 1 15 11 1 15 11 1 15 11 1 15 11 1 15 11 1 11 1 15 11 1 15 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 15 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1 11 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

istakingphotoremainPowerPercent remainLifePercent currentCurrent currentElectricity currentVoltage batteryTemperature dischargeCount flightmode isMotorsOn 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 82 100 64661 3528 16114 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 82 100 64661 3528 16114 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54188 64661 3485 3528 1545016114 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 82 100 64471 3528 16120 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 82 100 64471 3528 16120 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 82 100 64471 3528 16120 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Auto_Takeoff1 0 3 GS_Mode_Waypoint 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 82 100 64471 3528 16120 3041 3 GS_Mode_Gps_Atti 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 1 0 81 82 100 100 54747 64471 3485 3528 1546716120 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54747 59014 3485 3528 1546715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54747 59014 3485 3528 1546715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54682 59014 3485 3528 1545715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54682 59014 3485 3528 1545715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 0 81 82 100 100 54682 59014 3485 3528 1545715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54682 59014 3485 3528 1545715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 81 82 100 100 54682 59014 3485 3528 1545715809 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 1 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 59014 3528 15809 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 54481 3528 15573 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 54481 3528 15573 3041 3 GS_Mode_Gps_Atti 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 82 100 54481 3528 15573 3041 3 GS_Mode_Gps_Atti 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 1 0 82 100 54481 3528 15573 3041 3 GS_Mode_Gps_Atti 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 3 GS_Mode_Waypoint 0 80 82 100 100 54011 54481 3442 3528 1541915573 3051 3041 3 GS_Mode_Gps_Atti 1 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 0 82 100 54481 3528 15573 3041 3 GS_Mode_Gps_Atti 1 1 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 81 54188 3485 15450 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 81 54188 3485 15450 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54188 3485 15450 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54747 3485 15467 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 0 81 100 54682 3485 15457 3051 3 GS_Mode_Waypoint 1 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 1 p41 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 1 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 0 80 100 54011 3442 15419 3051 3 GS_Mode_Waypoint 1

Figure 40: Flight data’s sample extracted from the drone

6.0 TESTING THE SYSTEM’S PRECISION The first step towards the experiments is to test the accuracy of the above mentioned process. Building in an outdoor environment, relying on GPS coordinates to navigate the machine will most likely result in discrepancies between the planned and the actual trajectories. Using the above mentioned digital tools allows to clearly calculate the discrepancies and imprecision of this building process.

This thesis’ first protocol is to test the system’s precision. To do so a set of trajectories is drawn and sent to the quadrotors to be repeatedly flown 15 times each. Once done, the flight data is extracted from the machine and the flown paths are layered on top of the planned one. The result are rather positive showing an perpendicular displacements from the planned trajectories between +/-0m to +/-0.5m.

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6.1 Elements altering the precision The digital calibration’s tests shows results of a flying robot being approximately up to +/-0.5m precise. Here are the elements interfering with the building process’ precision.

Wind Load As expected, wind is one of the machine’s worst enemy. Whereas the quadrotors are equipped with algorithms counterbalancing the wind-loads, they still get off their trajectories, it can be a few centimeters to a few meters depending on the wind strength. Regarding the future of outdoor aerial construction it implies having to inevitably cope with wind.

Quadrotor’s velocity The experiences highlighted that the velocity of the machine has an impact on the precision of the flown trajectories. There is a right balance between a low velocity (1-2m/s) that leaves the aircraft to be most likely deviated with wind loads and high velocity (10m/s) that results in an aggressive behavior, lacking of precision at edge points. The experiments shows that a velocity of 4-5m/s is a good compromise in an outdoor context.

Changing ground surfaces The changing ground surfaces has a consequence over the visual odometry and the height of the building. When the machine flies over concrete and then grass, a change of altitude is observed at the threshold. Unifying the building surfaces can solve this issue.

Sequence: Drone changing depending on the ground surface

height

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6.2 Learning from the experiments: Autonomous flight behavior The first set of autonomous flights’ results shows that the waypoints navigation would need more fluidity. The drone would loose a precision and power by meticulously going from one waypoint to another, hovering for a long period on each point. The solution adopted to solve this problem is to fillet the trajectories’ corners in order to optimise the trajectories and achieve a smooth navigation.

Square edges experiment

y

y z x

Figure 41: Square trajectory view

x

Figure 42: Square trajectory plan with highlighted imprecise corners

z x

Figure 43: Square trajectory elevation

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Figure 44: Square trajectory velocity diagram showing constant acceleration and deceleration during the flying time.

Fillet edges experiment

y z

y x

Figure 45: Fillet corners trajectory view

x

Figure 46: Fillet corners trajectory plan

z x

Figure 47: Fillet corners trajectory elevation

Figure 48: Fillet corners trajectory showing a stable velocity during the flying time

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Square edges experiment

Quadrotors heads to following waypoint (X)

Stops

Rotates

Stops

Adjusts its position

heads towards the following waypoint (X) p46

Fillet edges experiment

Waypoint is taken as a reference for the drone’s autonomous trajectory. It flies smoothly along the filleted corners without changing velocity.

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6.3 Autonomous flight behavior: Measuring inaccuracy This calibration experiments allows to measure the exact inaccuracy of the flown trajectories. The flight data are exported to GrasshopperTM and the horizontal displacement is measured perpendicularly to the flight paths. This experiment also shows the limitations of the FlyLitchiTM software only importing and exporting heights in round meters.

lat -37.842891656883495 long 144.98059328645468 height 3m

8

lat -37.842929783207246 long 144.98056713491678 height 3m

5

lat -37.84289377501311 long 144.98054768890142 height 3m lat -37.842929783207246 long 144.98056713491678 height 2m

10

lat -37.842891656883495 long 144.98059328645468 height 2m

9

7

6 1

lat -37.842891656883495 long 144.98059328645468 height 1m

3

y z x

y z x

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lat -37.84289377501311 long 144.98054768890142 height 2m

lat -37.842929783207246 long 144.98056713491678 height 1m

2

lat -37.84289377501311 long 144.98054768890142 height 1m

a. The flight trajectories are drawn and translated into gps coordinates

b. The corners are filleted for smoother trajectories

c. The trajectories are flown and the recorded data is imported to GrasshopperTM

y z x

+/- 0.5m accuracy

+/- 0.15m accuracy

y x

z x

d. The horizontal displacement is measured perpendicularly to the drone’s trajectory

e. The heights’ exported data lacks of precision being recorded in round meters Figure 49-53: flight data exported to GrasshopperTM (top to bottom: perspective, plan and elevation) p49

y

y z

x

x

Figure 54-55: In digital space Data extracted from the machine

y y z x

Figure 56-57: In real space Data altered to represent on-site empirical observations.

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x

6.4 Digital VS real space: An imprecise global positioning system However, if the digital analysis of the data extracted from the drones are showing good results going up to +/-.5m of horizontal discrepancies, the empirical observations made onsite during the experiments were less conclusive. These latest showed a constant deviation of the quadrotors of 1-4 meters off its planned trajectory. This experiments’ results show that the gps based autonomous navigation system is the source of this major discrepancy between the digital and the real world.

The flying robots are indeed performing well in following the sent waypoints, however the gps receiver embedded in the machine and the gps signal on site is not powerful enough to precisely define those points on real earth. The tested structure measuring less than 5 meters the precision asked to the machine is beyond its capabilities. Therefore, the gps based navigation is the most problematic issue preventing an accurate autonomous navigation system as developed for this thesis. For the future of outdoor aerial building processes using gps localisation, one of the solution to fix this issue would be to enhance the precision of position data by using a Real Time Kinematic (RTK).

Sequence: the drone gradually shifts from its initial trajectory until colluding with the tripods.

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6.5 Prototyping: Limitations in real world experiments Prototyping with drones in an outdoor environment is a high risk process. It involves to work with a trial and error approach and encounter a range of problems coming both from hardware and software issues.

Here are the main limitations encountered: Real world limitations - Wind: The limitations due to the wind loads were expected. The drone is equipped with algorithms that adapt the drone’s flight to prevent it from being displaced. However, these algorithms have limitations and it is dangerous for the machine to fly in a windy environment. Also the autonomous navigation and the wind do not go well together; while fighting the wind load, the machines was unable to position itself properly. For these reasons, prototyping is made impossible on windy days.

- Rain: The hardware embarked on the machine are not water friendly and it is impossible to run prototype during rainy days.

- Public space limitations: This is one of the main safety issue encountered during the prototyping phase.

Drones are dangerous machines as the propellers in motion can easily cut through almost anything. The prototypes were done in a public space as far as people as possible. Ovals and basket ball courts were good spaces. However dogs, kids and curiosity to a flying machine attracts people and autonomous flights had to be aborted to prevent accidents.

Software limitations: - 6 meters height calibration: The high controller transmitting the autonomous navigation procedures to the drones is handled by the FlylitchiTM software. To avoid any crash when starting an autonomous flight a standard procedure sets the first point at 6m above the ground. This proved to be problematic with handling the tension in the lightweight structure (see figure 60), as a result, the creation of a first hovering point to fix the rope was needed.

- Autonomous/manual security: Theoretically, when an autonomous flight is launched one can regain control over the machine by switching to manual control. However, during the experiments, it appeared to be less effective than the theory and every time regaining control was critical, it took at least 5 seconds to the machine to abort the mission.

Hardware limitations - 20 minutes flight time: the DJI Phantom 3 drone has a 20 minutes battery autonomy. This significantly reduces the amount of time spent on prototyping, since it needs to be charged a few hours between each utilisation. Also, some settings can only be adjusted when the machine is on and connected which reduces the flight time even more.

- GPS inaccuracy: The gps inaccuracy, constantly shifts the trajectories from 0-5 meters. The drone hits the set obstacles damaging its propellers (see figure 58). This could be solved by enhancing the gps signal with some RTK, however this system is extremely costly.

- Odometer: The odometry system embedded in the Phantom 3 has proven to be inaccurate. Depending on the luminosity or the ground surface, the drone’s real height is significantly different than the planned one and can drop unexpectedly.

- Roller: Finally, managing the rope’s tension was a delicate process. Being a passive roller, the right friction needed to be found to respond to the right torque to unroll the thread and build the structures. The experiments went from no tension (see figure 59) to too much tension (see figure 60).

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Figure 58: Crashed propeller

Figure 59: No tension

Figure 60: Too much tension p53

7.0 OUTDOOR BUILDING EXPERIMENTATIONS The strength of the prototype as a working methodology is that it supersedes representational strategies (drawings and scale models) with an artifact that predicts exactly architectural effect. This means a prototype helps to close the historical gap (unpredictability) between representation and built reality by offering a means to simulate it precisely in order to enable change or alteration. (Barkow, 2014) The construction system introduced in this thesis is now tested to build lightweight structures in an outdoor environment. As it started to emerge with the previous tests for the machine’s calibration, prototyping is crucial to understand the opportunities and limitations of drones in building processes and their future applications. The following experiments intends to exploit the quadrotors ability to reach any point in space and fly around existing objects to weave 3 different tensile structures. The experiments are the following: 1. a small surface structure woven between 4 sticks, 2. a cable beam structure woven between 2 sticks and 3. a prototypical cable beam bridge woven between 4 sticks.

7.1 Designing and building with imprecision Unlike robotic arms, drones in building processes are imprecise tools. Variations due to hovering and stabilization as much as gps inaccuracy are to be added to the above mentioned outdoor imprecisions. For these reasons, they must be used for a building technology that supports their range of uncertainty. Tensile structures are very good for imprecision but also regarding the low load bearing ability of drones. Some of the basic building elements defined by the Institute for Dynamic Systems and Control group(ETH) are used to weave the structures (see figure57).

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Figure 61: open cable beam structures

Figure 62: Library of building elements

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7.2 Experiment 1: Surface structure The first experiment run is a flat tensile structure, woven between 4 sticks placed 4 meters apart. This first benchmark has a rather simple flight path and the safe distance between the sticks and the flying machine can be adjusted whenever needed.

The aim is to observe how well the machine is performing and observe if a 1metre safety radius around the sticks is enough to absorb the uncertainty of the process.

The surface structure allows the rope to safely remain parallel to the ground and the drone’s propellers.

2.4

{4.8m, 0.0m, 1.5m} {-37.84438o, 144.980964o, 1.5m}

{4.8m, 4.8m, 1.5m} {-37.844337o,144.980964o, 1.5m}

1.2

{4.8m, 0.0m, 1.5m}

{4.8m, 4.8m, 1.5m}

Sticks

Safety radius

Intended result

y x

{0.0m, 0.0m, 1.5m} {-37.84438o, 144.980921o, 1.5m}

{4.8m, 0.0m, 1.5m} {-37.844337o, 144.980921o, 1.5m}

4.8

6.78

4.8

y x

{0.0m, 0.0m, 1.5m}

{4.8m, 0.0m, 1.5m}

From digital space to real space

Set uncertainty tolerance

Digitally set the sticks position and intended woven geometry.

Trace the uncertainty boundary around the sticks to avoid any

In a first stage the trajectory’s points are in a xyz space and

collision with the flying machines.

measurements are following the metric system.

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2

{-37.844391, 144.980975, 1.5}

1 {-37.844391, 144.980953, 1.5}

3

{-37.844369, 144.980975, 1.5}

8

{-37.844348, 144.980975, 1.5}

4

10 {-37.844326, 144.980953, 1.5}

{-37.844369, 144.980953, 1.5}

5

Waypoints

11

{-37.844391, 144.980932, 1.5}

9

{-37.844326, 144.980975, 1.5}

{-37.844348, 144.980932, 1.5}

Final path

14 {-37.844326, 144.980932, 1.5}

y

y x

x

6 {-37.844391, 144.98091, 1.5}

7 {-37.844369, 144.98091, 1.5}

12 {-37.844348, 144.98091, 1.5}

13 {-37.844326, 144.98091, 1.5}

Set the waypoints for the autonomous navigation

Optimise flight path

Place the points around the safety boundary, they are now

Optimise the trajectories by filleting the corners and achieve a

forming the base for the quadrotor’s trajectory.

smooth flight path.

Figure 63-66: Surface structure’s scheme

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7.3 Experiment 2: Cable beam structure The second experiment intends to build an open cable structure. It is a 5m spanning structure built between two vertical sticks. The vertical geometry implies extra caution while building the structure to avoid the thread to getting stuck in the drone’s propellers. The construction sequence is made of 3 stages: 1. build the bottom thread, 2. then the top thread and 3. weave the bracing thread to tighten the structure.

y z

y z x

x

View of the intended result

Element n. 1: build the bottom thread and manually anchor it to the ground

z x

Elevation of the intended result

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y z

y z x

x

Element n. 2: build top thread and manually anchor it to the ground

11 7

Element n. 3: build the bracing thread

12

8 14 17

10

15 18

13 16

9

4 1 (lat, long, height)

6 3 5 2

y z

y z x

x

Bracing thread’s waypoints

Fillet the path Figure 67-73: Cable beam structure’s schemes

7.3.1 Reaching the limits of the gps system This experiment was successful until the implementation of the sticks. As soon as the drone needed to fly around a solid element, it became clear that the gps accuracy was too low to build autonomously. Indeed, the drone’s trajectories gradually shifted until continuously colluding with the solid elements.

Given the autonomous navigation clear limitations due to the gps inaccuracy, the next experiments are built with drones’ manually controlled trajectories, another possibility of the navigation software. It allows the quadrotors trajectories to be first flown and recorded, before being autonomously repeated by the quadrotor to weave the structures.

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7.4 Experiment 3: Cable beam bridge Initially, one of the aim of this thesis was to build an outdoor cable beam bridge. The experiment intended to show a real scale architectural outcome made possible by flying machines. Theoretically, our hardware should have made it possible, however, through the experimentation, it became gradually clear that lack of accuracy of the gps system and the imprecision of the height odometry system on the DJI Phantom 3 would not permit it. Nonetheless, with better hardware, the structure could be easily built. As a proof, the Dynamic System and Control in Zurich built one of these in September 2015.

The bridge is made of the two previous experiments: 2 open cable beams nets and one surface structure as a horizontal support. It is a rather complex geometry to achieve with a flying machine, the major difficulty being to weave the surface structure between the bracing elements. The building process is the following:

y z

y z x

Previously built cable beam structure

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x

Stage 1: Doubling the supports

y z

y z x

Stage 2: Doubling the cable beam structure

x

Stage 3: Building the surface structure between

Figure 73-76: Cable beam bridge schemes

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PART 3:

TOWARDS FUTURE APPLICATIONS

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8.0 BROADENING THE ARCHITECTURAL POSSIBILITIES “Every new production medium is first applied in the same way as the previous one, before the technology’s actual inherent potentials find expression.” (McLuhan, 1987).

“The historical development of the building industry shows that every innovation in construction technology needs at least one generation to establish itself, no matter how ground- breaking the first experiments or prototypes may have been.” (Bock & Langenberg, 2014) It is hard to predict with exactitude the future of drones in the architectural field. With prototypes such as the bridge built fully autonomously at the ETH (D’Andrea & al., 2015) and spanning more than 7metres, we are getting closer to a real scale application of flying robots. Drones are now part of the mainstream culture and are an extremely fast evolving technology, being the interest of groups of research in architecture and engineering, companies but also makers. In the span of 3 months that lasted this thesis, major software/hardware and research advancement have been made pushing the limits of the technology. At the edge of the architectural field, drones are already used for aerial surveying or 3d mapping (Pix4D, 2015). In the building processes, drones need to be considered not as a tool to replace human workforce and what already exists but as a problem solver tool to broaden the architectural possibilities.

8.1 Building remotely This thesis has demonstrated that outdoor autonomous flight is possible if the gps signal is enhanced and more accurate. The process developed to enable outdoor autonomous building has the ability to be fully off-site monitored. Since drones are intrinsically good at accessing remote sites, they must be used to do so. At large scale, they can build in inaccessible and hostile sites in steep mountains. They can build bridges across valleys, or nets to protect the fall of small rocks. They can also contribute to the rebuilding of unsafe places after a natural disasters. Drones can also intervene on closest inaccessible sites such as for restoration works in churches, ruins or industrial parks. Their ability to fly allows to build without any scaffold or cranes and makes the work cheaper and less dangerous for the surrounding built elements.

Finally, flying machines equipped with Lidars (integrated radars) are starting to be able to autonomously discover new spaces and to find their way through them. This kind of technology allows interventions in spaces that have never been accessed by humans.

8.2 Mixing technologies: towards a hovering world Drones are general-purpose machines. Hence, the possibilities given by the customisation of the machines are infinite. With a suitable tool, a drone is able to manipulate any material for a bespoke constructive process. In the future, drones in building processes will be equipped with a kit of modular parts, including grippers, material feeders and feedback sensors (Budig & al. 2012). But digital fabrication technologies could also be merged with flying machines and overcome their spatial limitations. Maybe in the future, 3d printers, cnc routers, laser cutters and robotic arms could be embarked on flying machines and therefore be freed from their p64

restricting frames. Such hybrid technologies have been successfully tested by the MIT Mediated Matter Group with their Robotic Swarm printing (Oxman & al., 2014) and the future resides in a problem solving approach to technologies.

8.3 Robotic intelligence: Swarm and 3d mapping It is unlikely that drones in building processes will be resumed to one specific tasks.

They will rather be able to perform a wide range of actions. The potential of machines on construction sites will be fully unlocked when robots will work in a swarm behavior.

Arriving to this level of technological advancement means that they will be fully autonomous and responsive both to each other and to their environment. In the case of using drones for a restoration work in a dome, this would be the overall process: Step 1: Surveying Drone as flying eyes and scanners Some drones fly autonomously up to the dome to scan and collect images of the space and issues. They remotely send the information to the ground station where humans are. Based on the information sent by the machines, an intervention can be done and sent to be executed by the machines.

Step 2: Image analysis, 3d visualization from the scans Architects visualize on their screens the images collected by the drones. A 3d model is automatically built from the images and scans.

Step 3: Planning Architectural decisions are made to solve the problem.

Having the accurate 3d model of the dome, architects can design the interventions (i.e. supports can be modeled on the edge of the dome and a net can be autonomously woven between those) Step 4: drones’ intervention The drones fix the supports build the net in a swarm like behavior.

Conclusion The experiments presented in this paper demonstrate the ability of quadrocopters to build tensile structures in an outdoor environment. There are however limitations in the accuracy of this process: some of these such as the gps inaccuracy can be easily overcome by enhancing its signal, while some others, such as wind load, are natural forces and the technology will need to overcome these issues in the future. This thesis also demonstrated a process to extract and analyse data from the quadrotor and a simple way, using architecture softwares, to remotely and autonomously navigate drones. These experiments have been done using only mainstream hardware and hacking their initial use with architectural softwares and tools. Even if their accuracy is not yet usable for architectural purposes, it is thrilling to imagine what can already be achieved with non professional equipment. Therefore, it is without any doubt that in a near future, drones will be enabling digital fabrication and automation to be finally performing well in on-site building construction. These milestones are a step further towards real-world scenarios of drones’ uses in the building processes. p65

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Architectural Design, “Made by Robots: Challenging Architecture at a Larger Scale”, Volume 84(3). New York: John Wiley & Sons. pp 22–43 Cache, Bernard. & Beaucé, Patrick. 2007. Objectile. Wien : Springer.

Carpo, Mario. 2009. Revolutions: Some New Technologies in search of an Author. LOG 15. New York: Anyone Corporation. pp.49–54.

Carpo, Mario, 2012. Digital Darwinism: Mass Collaboration, Form-Finding and the Dissolution of Authorship.

LOG 26, New York: Anyone Corporation. pp.97–105.

Carpo, Mario, 2008. Non Standard Morality: Digital Technology and its Discontents. In A. Vidler, ed.

“Architecture Between Spectacle and Use”. New Haven: Yale University Press for the Clark Institute.

Dunn, Nick. 2012. Digital Fabrication in Architecture. London: Laurence King Publishing Fleischmann, Moritz, Knippers, Jan, Lienhard, Julian, Menges, Achim and Schleicher, Simon. 2012.

Material Behaviour: Embedding Physical Properties in Computational Design Processes. Architectural Design “Material Computation: Higher Integration in Morphogenetic Design”. Volume 82(2). NewYork: John Wiley & Sons. pp.44–51 Goulthorpe, Mark, 2008. The possibility of (an) architecture, London: Routledge.

Graf, Fritz . 1993. Greek mythology : an introduction. Baltimore: Johns Hopkins University Press.

Gramazio, Fabio, Kohler, Matthias and D’Andrea, Raffaello. 2013. Flight Assembled Architecture.

Orléans,France: Editions Hyx. Gramazio, Fabio, and Kohler, Matthias, Helm, V. & Ercan, S. 2012. Mobile robotic fabrication on construction sites: DimRob”. in Proc. IEEE/RSJ Int. Conf. Intelligent Robots Systems, Vilamoura, Portugal, pp. 4335–4341.

Gramazio, Fabio & Kohler, Matthias. 2008. Towards a Digital Materiality. In B. Kolareveric & Kevin Klinger (eds.) Manufacturing Material Effects: Rethinking Design and Making in Architecture. New York: Routlege, pp. 103–118.

Gramazio, Fabio & Kohler, Matthias. 2008. Digital Materiality in Architecture, Baden, Switzerland: Lars Müller.

Gramazio, Fabio & Kohler, Matthias. 2012. Aerial Robotic Construction Towards a New Field of Architectural Research, International Journal of Architectural Computing, 10(3), pp. 439–460.

Gramazio, Fabio & Kohler, Matthias. 2014. The robotic touch : how robots change architecture. Zurich Park Books Gramazio, Fabio & Kohler, Matthias. 2014. The flight assembled architecture installation. IEEE control systems magazine.

Linner, Thomas. 2013. Automated and Robotic Construction: Integrated Automated Construction Sites. dissertation. Technical University of Munich Hu, Jost. 2006. The introduction of reinforced concrete in Switzerland (1890–1914): Social and cultural aspects. in M Dunkeld et al (eds). The Second International Congress on Construction History. London: Routledge. pp 1741–53.

Iwamoto, Lisa. 2009. Digital Fabrications: Architectural and Material Techniques. New York: Princeton Architectural Press Kohler, Matthias. 2012. Aerial Architecture. Log 25. New York: Anyone Corporation. pp23-30 p66

Kolarevic, Branko. 2003. Architecture in the Digital Age: Design and Manufacturing, Spon Press.

Marble, Scott (ed.). 2012. Digital Workflows in Architecture, Basel : Birkhäuser Lindsey, Quentin, Mellinger, Daniel & Kumar, Vijay. 2012. Construction of Cubic Structures with Quadrotor Teams. Mechanical Engineering and Applied Mathematics. University of Pennsylvania Lloret Kristensen, Ena, Gramazio, Fabio & Kohler, Matthias, Langenberg, Silke. 2013. Complex concrete constructions - merging existing casting techniques with digital fabrication in Open Systems: proceedings of the 18th conference on CAADRIA 2013, Hong Kong, pp. 613-622 Markoff, John. 2013. Robot Makers Spread Global Gospel of Automation. The New York Times. pp.2013– 2016.

Augugliaro, Federico, Mirjan, Ammar, Gramazio, Fabio, Kohler, Matthias and D’Andrea, Raffaello.

2013. Architectural fabrication of tensile structures with flying machines, Green Design, Materials and Manufacturing Processes. Bártolo et al. (eds). London: Taylor & Francis Group Oxman, Neri. 2014. Programming Matter, Architectural Design, “Material Computation: Higher Integration in Morphogenetic Design”. 82(2), New York: John Wiley & Sons. pp.88–95 Oxman, Neri, Duro-Royo, Jorge, Keating, Steven, Peters, Ben & Tsai, Elizabeth. 2014. Towards robotic swarm printing. Architectural Design, 84(3), New York: John Wiley & Sons. pp.108–115.

Oxman, Neri, 2014. Silk Pavilion: a Case Study in Fibre-Based Digital Fabrication. In S. L. Fabio Gramazio, Matthias Kohler, ed. Fabricate: negotiate design and making. Zurich: Verlag, pp. 248–255.

Pedreschi, Remo. Form, Force and Structure: A brief History. Architectural Design. 2008. pp.12–19.

Picon, Antoine. Digital Architecture and the Poetics of Computation. Metamorph Focus: Katalog zur 9.

Architektur Biennale von Venedig. 2004. pp.58–69.

Picon, Antoine. 2014. Robots and Architecture: Experiments, Fiction, Epistemology. In Architectural Design “Made by Robots: Challenging Architecture at a Larger Scale”, Volume 84, Issue 3, New York: John Wiley & Sons. pp 88-89 Piroozfar, Poorang & Piller, Frank (eds). 2013. Mass Customisation and Personalisation in Architecture and Construction, London/New York: Routledge Preisinger, C., 2013. Linking structure and parametric geometry. Architectural Design, Volume 83(2), New York: John Wiley & Sons. pp.110–113.

Ruskin, John, (1900) The Seven Lamps of Architecture. Boston: Dana Estes & company Publishers, p. 36-37 Scheurer, Fabian & Stehling, Hanno. 2011, Lost in parameter space? Architectural Design, Volume 81(4), New York: John Wiley & Sons. pp.70–79.

Schumacher, Patrick. 2009. Parametricism: A new global style for architecture and urban design. Architectural Design, Volume 79(4), pp.14–23.

White, Duncan, Pollard, Stephen, Luebkeman, Chris & Hargrave, Josef. 2014. Rethinking the factory.

London: Arup Foresight + Research + Innovation 2013. Navy Basic Machines (NAVEDTRA 14037) - Nonresident Training Course. Naval Education and Training Professional Development and Technology Center.

2015. Phantom 3 Advanced User Manual v1.4. DJI Web: ARCAS. 2015. Aerial Robotics Cooperative Assembly system. Accessed 22 October 2015. http://www.arcasproject.eu/publishable-resources National Geographic. 2013. 5 Surprising Drone Uses (Besides Amazon Delivery). Accessed 20 October 2015. http://news.nationalgeographic.com/news/2013/12/131202-drone-uav-uas-amazon-octocopterbezos-science-aircraft-unmanned-robot/ Pix4D. 2015. UAV mapping software. Accessed 30 October 2015. https://pix4d.com/ Sturm, Jürgen. 2015. Autonomous navigation for flying robots. Technical Universty Munich. Accessed 20 October 2015. https://courses.edx.org/courses/course-v1:TUMx+AUTONAVx+2T2015/info TED. 2015. The future of flying robots. Accessed 22 October 2015. https://www.ted.com/talks/vijay_ kumar_ the_future_of_flying_robots#t-121777 TED. 2013. The astounding athletic power of quadcopters. Accessed 13 October 2015. http://www.ted.com/ talks/raffaello_d_andrea_the_astounding_athletic_power_of_quadcopters?language=en The Verge. 2015. DJI Phantom 3 review: the best drone you can buy just got even better. Accessed 13 October 2015. http://www.theverge.com/2015/8/7/9115449/dji-phantom-3-drone-review-price-quadcopterspecs

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Bock, T. & Langenberg, S., 2014. Changing building sites. Architectural Design, 84(3), pp.

88–99.

History/Mythology

Theory

Utopia

flying machines

Tom F Peters, Building the Nineteenth Century, MIT Press (Cambridge, MA), 1996.

Poorang AE Piroozfar and Frank T Piller (eds), Mass Customisation and Personalisation in Architecture and Construction, Routledge (London/New York), 2013 The International Association for Automation and Robotics in Construction, Robots and Automated Machines in Construction, Building Research Establishment Ltd (Watford), 1998.

White, D. & Pollard, S., 2015. Rethinking the Factory. Arup Foresight + Research + Innovation.

Innovation in Construction

History Robots in Construction Machines

Thomas Linner, ‘Automated and Robotic Construction: Integrated Automated Construction Sites’, dissertation, Technical University of Munich, 2013.

Markoff, J., 2013. Robot Makers Spread Global Gospel of Automation. The New York Times,

Course, N.T., 199

Anon, 1994. Henry Ford: Mass Production, Modernism and Design. , pp.124–143.

Voskhul, A., Androids in the Enlightenment:Mechanics, Artisans and Cultures of the Shelf, Chicago: Chicago University Press.

Rifkin, J., 1995. The End of Work.

R.E. Somol ed., 1997. Autonomy and Ideology: Positioning an Avant-Garde in America, Monacelli ., New York.

Maximal performance, minimal resources: Idea of gradient in materiality.

Programming matter following nature’s dialect and have not only homogeneous material but tailored to a situation. ie Gradient of porosity, gradient of elasticity. better structures, optimised .

Robots

Industrial Production General

Material Ecology natures artefacts are made of fibers.

Fibers distribute load equally (material engineer) and at the same time allow for food absorption, heat exchange, etc… (multifunctionality)

Addis, B., 2007. B design engineer London: Phaidon

Mark, R. ed., 199 up to the Scient Structure of Larg Cambridge/MA:

Construction

See “Architecture InFormation: On the nature of information in digital architecture”

Also see Kukkugia

Automation

CAD

Oxman, N., (2012) Programming Matter, AD 82, Material Computation: 88-95 She also appears in: Sigrid Brell-Cokcan, Johannes Braumann (eds.) (2013) Rob/Arch 2012 : robotic fabrication in architecture, art and design. Wien : Springer Oxman, N. et al., 2014. Towards robotic swarm printing. Architectural Design, 84(3), pp.108–115.

Oxman, N., 2014. Silk Pavilion: a Case Study in Fibre-Based Digital Fabrication. In S. L. Fabio Gramazio, Matthias Kohler, ed. Fabricate: negotiate design and making. Zurich: Verlag, pp. 248–255.

Neri Oxman Pop Tech Conference https://vimeo.com/7806194

Neri Oxman

Dunn, N. (2012 Architecture. L Publishing

Digital Fabrication

Iwamoto, L., 2009 Architectural an Architectural Pres

General

Marble, S., 2012. Digit

Kolarevic, B., 2003. Ar Design and Manufact

Fleischmann, M. & Kni Behaviour: Embeddin Computational Desig Design, 82(2), pp.44–5

Aerial Assembly Processes References’ Arborescence

Anon, 2014. The flight assembled architecture installation. IEEE contro systems magazine, (August).

This document maps out the references and sources I came across during the first 5 weeks of research for my thesis. It was created at a very early stage as a way to organize my readings

DRONES in construction processes

in a non-linear way. It also truthfully reflects the complexity of the network of disciplines that resulted in today’s use of unmanned aerial vehicles (UAV) in an architectural context.

The references are generally organized by themes

(CAD, Innovationainsubjective Construction, Automation, Bibliography: conceptual Digital Fabrication and Drones). map Coralie Ming

References as of today, 01 September 2015

p68

Gramazio+Kohler

Gramazio, F. and Kohler, M. (2012) ‘A Robotic Construction Towards a Ne of Architectural Research’, Internati Journal of Architectural Computing, 1 439–460.

Augugliaro, F. et al., 2013. Building t structures with flying machines. IEE International Conference on Intellige and Systems, pp.3487–3492.

Mirjan, A. et al., 2013. Architectural fabrication of tensile structures with fly machines, CRC Press.

Gramazio & Kohler, d’andrea, 2013. Fligh assembled Architecture, Paperback.

Kohler, M., (2012) “Aerial Architecture” 25, pp23-30

Da Vinci + Frei Otto + Buckminster Fuller Nervi + Maillart

The design and the construction processes closely related.

Anon, 2008. Form, Force and Structure: A brief History. Architectural Design, pp.12–19.

Innovation in construction, reinforced concrete

Preisinger, C., 2013. Linking structure and parametric geometry. Architectural Design, 83(2), pp.110–113.

Relevance between Design and Construction

Non-Standard

Mangelsdorf, W., 2010. Structuring strategies for complex geometries.

Architectural Design, 80(4), pp.40–45.

Cache, B. & Beauce, P., 2007. Vers un mode de production non-standard. In Fastwood: Un Brouillon Project. Institute for Cultural Policy, pp. 6–8.

Bollinger, K., Grohmann, M. & Tessmann, O., 2010. Structured Becoming. Architectural Design, 80(4), pp.35 – 39.

Addis, B., 2013. “Toys that save millions” - A history of using physical models in structural design. Structural Engineer, 91(4), pp.12–27.

few interesting stuff about models an form finding.

Terzidis, K., 2006. Algorithmic Architecture, Oxford: Architectural Press.

Balmond, C., 2002. Informal, Munich ; New York: Prestel.

94. Basic Machines.

Weinstock, M., 2004. Morphogenesis and the Mathematics of Emergence. In M. Hensel, M, Menges, A.Weinstock, ed. Architectural Design. John Wiley & Sons, p. 17.

basic mechanical principles

Other References

Building: 3000 years of ring and construction, n.

93. Architectural Technology tific Revolution: The Art and ge-Scale Buildings, MIT Press.

General

Pask, G., 1967. The Architectural relevance of Cybernetics. Architectural Design, September, p.496.

Lynn, G., 1998. Folds, bodies & blobs, Brussels: La lettre volée.

Mitchell, W., 1990. The logic of architecture, Cambridge MA: MIT Press.

Breaks down architecture components into their basic principles. Basically what is done today in parametric design.

Aranda/Lasch, 2006. Tooling, New York: Princeton Architectural Press.

Probably not that relevant to the thesis

Goulthorpe, M., 2008. The possibility of (an) architecture, London: Routledge.

(DECOi) interesting practice

9. Digital Fabrications: nd Material Techniques, Princeton ss.

Carpo, M., 2012. Digital Darwinism: Mass Collaboration, Form-Finding and the Dissolution of Authorship. LOG 26, pp.97– 105.

Lynn, G. ed., 2013. Archeology of the Digital, Berlin: Sternberg Press.

Carpo, M., 2011. The Alphabet and the algorithm, Cambridge MA: MIT Press.

tal Workflows in Architecture,

Scheurer, F. & Stehling, H., 2011. Lost in parameter space? Architectural Design, 81(4), pp.70–79.

rchitecture in the Digital Age: turing, Spon Press.

ippers, J., 2012. Material ng Physical Properties in gn Processes. Architectural 51.

Kohler, M., Gramazio, F. and Willmann, J. (2014) The Robotic Touch: How Robots Change Architecture.

Switzerland: Park Books.

Technical Article

De re edificatoria, ed giovanni Orlandi (Milan: il Politiflio, 1966)

Oxman is said to be an example of . Called “Intelligent design” “Performative behaviour of materials”

“the capacity to algorithmically manipulate a large amount of data in the virtual space of the computer has made it possible to overcome not only the design principles of Modernism but also their standardised industrial forms of production”

M. Burry, 2011. Scripting Cultures: Architectural Design and Programming. , pp.27–71.

On language: Middle age = the parallel between the master builder passing oral info to the craftsmen // Now = the computer to the robot.

Davis S.M (1987). Future perfect, Reading, MA, Addison.Wesley Publishing Company, Ruskin, J., (1900) “The Seven Lamps of Architecture” Boston: Dana Estes & company Publishers, p. 36-37

Walter Benjamin, “a work of art in the age of mechanical reproduction, 1936

Aerial ew Field ional 10(3), pp.

15th century: Leon Battista Alberti claimed: “architect should stop making things, and that they should design things instead.”

Introduction of task division that is disappearing now with digital architecture

Carpo, M., 2008. Non Standard Morality: Digital Technology and its Discontents. In A. Vidler, ed. Architecture Between Spectacle and Use. New Haven: Yale University Press for the Clark Institute.

Kohler, Gramazio,… (2013) “complex concrete constructions - merging existing casting techniques with digital fabrication” in Open Systems: proceedings of the 18th conference on CAADRIA 2013, Hong Kong, pp. 613-622

Gramazio+Kohler

ol

Negroponte, N., 1996. Being Digital, New York: Vintage Books.

Carpo, M., 2009. Revolutions: Some New Technologies in search of an Author. LOG 15, pp.49–54.

Davis, D., 2013. Modelled on Software Engineering : Flexible Parametric Models in the Practice of Architecture.

Schumacher, P., 2009. Parametricism: A new global style for architecture and urban design. Architectural Design, 79(4), pp.14–23.

2) Digital Fabrication in London: Laurence King

Picon, A., 2010. Digital Culture in Architecture: An Introduction for the Design Professions, Birkhäuser Verlag AG.

Picon, A., 2004. Digital Architecture and the Poetics of Computation. Metamorph Focus: Katalog zur 9. Architektur Biennale von Venedig, pp.58–69.

1987 First appearance of the term “Mass Customisation” individual products can be made as economically as comparable mass-produced articles 19th c. it was the transition from traditional materials to steel and glass and to industrial machine production which provoked an intense discussion about the relation between architecture and its making

On the introduction of feedback loop in casting systems. Non linearity in the flow of information, feedback loops and talking material.

The technology does not develop in isolation from its cultural context, it emerges out of a process of dirfferentiation with all the associated social, political and economic interaction

in architecture the poetics of computation have not yet fully developed.

Heretofore, digital architecture has exhausted itself, intoxicated by the possibilities of generating complex geometries

Picon, A., 2014. Robots and Architecture: Experiments, Fiction, Epistemology. In Architectural Design. John Wiley & Sons.

tensile EE ent Robots

Made by robots

Budig, M. & Lim, J., 2012. INTEGRATING ROBOTIC FABRICATION IN THE DESIGN.

ying Kohler, G.&, 2008. Digital Materiality in Architecture, Baden, Switzerland: Lars Müller.

ht

Log

New design methodology is evolving, one open to envisioning architecture not only as a final form but as a complex and refined generative process of robotic materialisation.

Gramazio, F. & Kohler, M., 2008. Towards a Digital Materiality. In B. Kolveric & Kevin Klinger, eds. Manufacturing Material Effects: Rethinking Design and Making in Architecture. New York: Routlege, pp. 103– 118.

references mid sem - 01 Sep 2015p69 09:20 ©

Images’ sources Figure 1: http://www.museodelprado.es/imagen/alta_resolucion/P01540_01.jpg, last accessed 28/10/2015 Figure 2: https://michelleipeters.wordpress.com/category/uncategorized/ Figure 3: http://www.arch.mcgill.ca/prof/sijpkes/abc-structures-2005/concrete/history-of-concrete_files/concrete.html Figure 4: http://www.bdonline.co.uk/photographs-of-italian-modernism-are-on-a-mission-to-influ- ence/3140605.article Figure 5: http://www.impresedilinews.it/a-varese-lomaggio-a-nervi/ Figure 6: http://summerandmadness.tumblr.com/post/35645833011/palazzo-dello-sport-roma-pier-lui- gi-nervi Figure 7: http://www.archilab.org/public/1999/artistes/obje01en.htm Figure 8: https://www.flickr.com/photos/boldtoad/3116169070 Figure 9: http://urizen.blog.anous.fr/4236/MUR-DE-BRIQUES-COURBE/ Figure 10: http://www.dailytonic.com/pike-loop-manhattan-new-york-by-gramazio-kohler-architecture-and-digital-fabricationeth-zurich/ Figure 11: http://www.gramaziokohler.arch.ethz.ch/web/d/forschung/223.html Figure 12: http://www.gramaziokohler.arch.ethz.ch/web/d/forschung/223.html Figure 13: http://news.mit.edu/2011/3d-printing-0914 Figure 14: http://matter.media.mit.edu/tools/details/3d-printing-of-functionally-graded-materials Figure 15: Coralie Ming.

Figure 16: http://www.remixtheschoolhouse.com/tags/collage Figure 17: http://medias.lemonde.fr/mmpub/edt/pf_son/xml/20050708/portfolio_670706.xml Figure 18: http://arqueologiadelfuturo.blogspot.com.au/2010_06_01_archive.html Figure 19: http://arqueologiadelfuturo.blogspot.com.au/2010_06_01_archive.html Figure 20: http://reviews.mtbr.com/lily-follow-me-camera-drone-flies-itself/lily-hand Figure 21: http://www.blomasa.com/ Figure 22: http://www.engadget.com/2009/11/18/3d-mapping-drone-fires-off-lasers-from-a-mile-away- video/ Figure 23: http://www.jcmagazine.com/dhl-inicia-servicio-de-mensajeria-con-drones/ Figure 24: http://www.4erevolution.com/flyability-drones-for-good/ Figure 25: http://altigator.com/drones-for-search-rescue-missions/ Figure 26: http://www.aerialtronics.com/videos/aerialtronics-altura-zenith-used-for-ava- lanche-search-rescue/ Figure 27: http://www.wireless-mag.com/News/37924/cyberhawk-looks-to-boost-business-in-interna- tional-utilities-sector. aspx Figure 28: http://www.hdwallpapersimages.com/rhinoceros-00977/146375/ Figure 29: http://raffaello.name/projects/flight-assembled-architecture/ Figure 30: http://www.gramaziokohler.com/web/e/projekte/209.html Figure 31: http://www.semageek.com/quand-les-drones-quadrotor-du-grasp-lab-se-mettent-a-la-construction/ Figure 32: https://www.youtube.com/watch?v=_T0J5PB2av8 Figure 33: http://www.kokkugia.com/AADRL-aerial-robot-thread-construction Figure 34: https://www.youtube.com/watch?time_continue=1&v=CCDIuZUfETc Figure 35a: http://www.infohightech.com/des-robots-volants-construisent-une-tour-de-6-m-de-haut/ Figure 35b: http://aeromodelismiramar.blogspot.com.au/2012_01_01_archive.html Figure 36: http://www.lmt.ei.tum.de/team/mitarbeiter/sebastian-hilsenbeck.html?type=98 Figure 37: http://www.brandsmartusa.com/DJI/185061/Phantom+3+Professional+Quadcopter+ With+4K+Camera.htm Figure 38: http://www.dronesvision.net/tw/dji-phantom-3/2236-dji-phantom-3-part-1-gps-module.html Figure 39 to 60: Coralie Ming Figure 61: Augugliaro, Federico, Mirjan, Ammar, Gramazio, Fabio, Kohler, Matthias and D’Andrea, Raffaello. 2013. Building tensile structures with flying machines. IEEE International Conference on Intelligent Robots and Systems. Tokyo, Japan. pp.3487–3492.

Figure 62: Sandaker, Bjorn. Eggen, Arne & Cruvellier, Mark. 2013. The structural basis of architecture. Routledge.

Figure 63 to 76: Coralie Ming

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