XO Thesis by Suz Ibrahim

ALEKSANDAR BURSAC, GEORGIA TSOLI, LISA KUHNHAUSEN, SUZAN IBRAHIM

TEAM Aleksandar Bursac Georgia Tsoli Lisa Kuhnhausen Suzan Ibrahim TUTOR/PROGRAM DIRECTOR Theodore Spyropoulos ASSISTANTS TUTOR Mustafa El-Sayed Apostolos Despotidis SUPPORTED BY AKT II Consulting Structural and Civil Engineers, London 2015-2016

Architectural Association School of Architecture Design Research Laboratory

CONTENT STUDIO BRIEF 43

XO 45

REFERENCES 46

ESSAYS

WHY LOOK INTO BIOLOGICAL SYSTEMS? 54 SEEING THE FOREST FOR THE TREES 60

MOBILITY / SELF ASSEMBLY

TWO SPECIES 62 GRIPPER 74 SPHERE 108

SPECIE COMMUNICATION 132

BODY PLAN FORMATION

SELF STRUCTURING

138

STRUCTURING 174

POPULATION COMMUNICATION 200

GROWTH STRATEGY 228

FINAL THOUGHT FOR A NEW START 244

SOURCES 246

[Foreword]

FOREW0RD A Hundred Seventy Five Words Towards A Human and Machine Ecology The fixed and finite tendencies that once served architecture have been rendered obsolete. Today the intersections of information, life and matter display complexities that suggest the possibility of a much deeper synthesis. Architecture finds itself in an increasingly polarized world of conservative and habitual response. The necessity to experiment, to propose and construct alternative models and environments has never been more urgent. Set within in this context the AADRL operates as a framework to create a space for this next generation of radical architecture to be fostered. As science fiction has become fact the domain of behavior and time are the mediums of our architecture today. In the spirit of this pursuit XO sits in an uncomfortable world that by necessity needs to challenge convention and our definitions of what architecture can be. It is in this uncomfortable place where the potential for innovation lay. Architecture in an expanded field of understanding is at the heart of a shared pursuit to allow new potential for the construction of a participatory space in an ever latent and uncertain world. Theodore Spyropoulos AADRL Director

[Studio Brief]

STUDIO BRIEF Constructing Frameworks The studio has historically pursued an active engagement into constructing environments that build intimate relationships between things. Fostering a behavioural discourse that has explored adaptive ecologies, robotic agency, material computation and participatory frameworks, the studio understands architecture and urbanism as an experimental spatial framework of communication. Through poly-scalar relationships, the studio works between scales and forms of production that facilitate an understanding of the interrelationships between design systems. Through the development of a time-based framework for understanding design within environments of engagement we pursue an active exploration of how architecture can participate within larger ecologies bridging conventional divides of what is understood as natural, machinic and the man-made. Our interests are to explore architecture as a lifelike agent that embodies active and dynamic correlations with its environment. Our approach looks towards machine-to-machine, machine to human and human-to-human forms of interaction.

and through this engagement constructs a means to explore and operate within it. The aim is to build mechanisms that foster intelligence through a system;s ability to create frameworks that examine forms of control and address issues of latency and the unknown. The studio fundamentally challenges the fixed and finite orthodoxy of design and implementation towards a behavioural model of architecture. To this aim learning is a subject of enquiry. How can our design systems lean from their environment and act within it? The studio will explore this as a conceptual and operational driver to explore real-time sensing and vision systems within our architecture. Self-Aware - Self-Assembled Architecture in our studio is not holistic in form but rather is a product of continuous formation. Our systemic conceptions have the capacity to be deployed, form and reform. The ambition is a move towards architectural systems that have the capacity and intelligence to actively operate as mobile infrastructures that respond to information that is social, climatic and speculative in constraint. The studio will explore enabling agents that develop deeper set of relations, exploring prototypes that are robotic in nature, simulation as ecologies of relations and systems that are deployable through emergent interactions.

Autonomous Learning Systems Our current research examines systems that are developed to actively engage with the world

[XO]

XO We see softness as a property that allows for volatility and change in the system. It tolerates a higher level of inexactitude showing great potential to use redundancy as a method to ensure the viability of many outcomes and increase the possible solution space of soft systems. Because softness does not necessarily work with fixed arrangements but rather goes through temporary stages of varying stability, it always presents itself as volatile inhabiting the gradient space between liquid and solid, chaotic and ordered, stable and unstable. Therefore the interest in our research lies in investigating softness both materially and programmatically, through a self-regulated system that exploits these properties as a technique to deal with problems of mobility, formation and structuring. To achieve these goals we employ communication strategies which delineate different levels of organization and association in the system based around the idea that they are exerted on speciated ecology. This ecology comprises two distinct interacting taxonomies which, with separate goals and abilities and division of labour, form symbiotic relationships governed by the rules of interactions that enable them to deal with problems more complex than any single representative of either taxonomy could overcome. The system therefore becomes an exploration into affiliations and collaborative efforts predicated upon establishing temporary relationships in the ecology, where information exchange creates outcomes that get inscribed into the system as a difference in material property and choreography the actors in the system undertake.

[References]

Image: Karl Sims (snapshot from video)

Sims, K., 1994. Evolved Virtual Creatures, Evolution Simulation, 1994. “...a school of swimming “water snakes”...”

[References]

KARL SIMS ...it might be easier to evolve virtual entities exhibiting intelligent behavior than it would be for humans to design and build them. 1 We look into Karl Simsâ&#x20AC;&#x2122; virtual creatures as a computational experiment situated next to what we are doing. His creatures are evolved to perform specific tasks in simulated visual environments, such as swim, jump, walk. And they have a goal; to gain control over a common resource. But how could we efficiently create rules for the development of creatures starting with basic components with minimum agency? Sims is addressing a genetic language that uses nodes and connections to exhibit a variety of morphologies and behaviors. In our case mobility is the main driver for the creation of different aggregations of units, what we call bodies. We are interested in an ecology of bodies learning to approach through communication with the goal of generating atmospheres, ambiance, or microclimate while achieving and maintaining structural performance combining morphology and control. As the success of the strategy is often highly dependent on the morphology of the body we explore a taxonomy of different body formations.

1 Sims, K., 1994. Evolving virtual creatures. Proceedings of the 21st annual conference on Computer graphics and interactive techniques - SIGGRAPH â&#x20AC;&#x2DC;94

[References]

uniform field of cells

differentiation

inhibit neighbor differentiation

patterns of goal oriented cells

communication field

EGG

units/particles

LARVA

PUPA

bodies

FLY

Image( left):Endless Forms Most Beautiful, Sean Carroll

CELL DIFFERENTIATION â&#x20AC;&#x153;In an initially uniform field of cells, two cells begin to differentiate and inhibit cells in contact with the from doing so. Cells in other regions begin to differentiate and inhibit their nearest neighbours, which eventually establishes a regularly spaces pattern of cells. These cells now may form bristles, feathers, or other structures.â&#x20AC;? - Sean Carroll (pg.104) pp. 63, 93

[References]

EVO DEVO Evo Devo has been one of our core references. With this we have paid special attention to the process of cell differentiation within a homogenous system. Through embedded information within the cell and communication with its environment, the cell becomes specialized over a period of time to form specific tissues, organs and by extension organisms that perform different tasks.

[References]

Image: Harvard Whitesides Group (snapshot from video)

SOFT ROBOTICS WHITESIDES RESEARCH GROUP Harvard University,. Harvard Researchers Demonstrate Soft Robot Camouflage System. 2012. Web. 1 Feb. 2016.

[References]

HARVARD Harvardâ&#x20AC;&#x2122;s Whitesides Research Group has investigates soft robotics at singular level. They have focused on the specific soft qualities of the robots such as gestures and mobility. We find this research a good foundation in soft robotic, but our emphasis has been to explore soft robotics that form higher levels of organizations of populations.

[References]

Image: Festo (snapshot from video)

FESTO Pneumatic worm.

[References]

FESTO Festo provided another good example into soft robotics and highly controlled actuation. We find their work on jamming specifically interesting because it addresses changing material properties though actuation.

[Essays]

WHY LOOK INTO BIOLOGICAL SYSTEMS? The apparent veil between the organic and the manufactured has crumpled to reveal that the two really are, and have always been, of one being. What should we call that common soul between the organic communities we know of as organisms and ecologies, and their manufactured counterparts of robots, corporations, economies, and computer circuits? I call those examples, both made and born, “vivisystems” for the lifelikeness each kind of system holds.1

i. Homeostasis ii. Organization iii. Metabolism iv. Growth v. Adaptation vi. Response to stimuli vii. Reproduction2 Perhaps, in order to establish a new model of life more in line with the “born/made” pathos Kelly expresses in his writings, a subtle reworking of these characteristics is necessary. Some of the traits Furler outlines are already seen as an inevitable necessity for the proposed system. In truth, the only two that will not be discussed are Growth and Reproduction and even these will be addressed in way. The amended tenets of life to be applied to the artificially constructed system would therefore be as follows:

It is, after all, a completely valid question to ask – why look at biological systems at all? The fad of biomimicry that originates from the 60s is all but over, so why give Mother Nature the time of day when conceptually, stylistically and functionally we have struggled for decades to resolve the strange dialogue between natural and technological systems within the scope of the architectural discourse.

i. Homeostasis [efficacy] – maintaining an energy efficient state

Likely as one might be to dismiss this attempt as marginal or as downright misguided, Kelly raises a valid point in his book addressing the “made” and the “born” as concepts that are experiencing a semantic overlap in the 21st century. The act of making today is so much more alike to the act of birthing that it makes perfect sense to look for input in the original Parent. Side-stepping the generally confusing approach of sampling nature as a style rather than a phenomenon of performative and procedural value, we focus our research on the social behaviour of colonial organisms.

ii. Organization [autonomy] – propensity towards self-sufficient organizational qualities facilitated through communication patterns

It may not be easy to give an explicit definition to life, but biologically it is generally accepted that in order for something to be “alive” it must possess all, or at the very least most of these characteristics:

v. Response to stimuli [sensory sensitivity] – ability to sense and recognize its environment and human agency

iii. Metabolism [energy-flow] – transformation of energy in order to move, construct and space-make iv. Adaptation [transformable properties] – ability to assume new configurations in response to environmental change and human agency

1 Kelly, K. (1994). Out of control. Reading, Mass.: Addison-Wesley, p.7.

associated with life. iv. Maintenance of a higher rate of anabolism than catabolism. A growing organism increases in size in all of its parts, rather than simply accumulating matter. v. The ability to change over a period of time in response to the environment. This ability is fundamental to the process of evolution and is determined by the organism’s heredity as well as the composition of metabolized substances, and external factors present. vi. A response can take many forms, from the contraction of a unicellular organism to external chemicals, to complex reactions involving all the senses of multicellular organisms. A response is often expressed by motion, for example, the leaves of a plant turning

2 Lance Furler, R. (2015). Origin of Life, Sustainability, Energy, and IronSulfur World Theory [online] Robertlfurler.com. Available at: http://www. robertlfurler.com/ [Accessed 17 Jul. 2015]. i. Regulation of the internal environment to maintain a constant state. ii. Being structurally composed of one or more cells, which are the basic units of life. iii. Transformation of energy by converting chemicals and energy into cellular components (anabolism) and decomposing organic matter (catabolism). Living things require energy to maintain internal organization (homeostasis) and to produce the other phenomena

[Essays] While the semantic framework developed to anchor the research may occasionally clash with the respective biological definitions, the ultimate intent was to build up a clear relationship between the system on all scales in terms of structuring, behavior and communication, rather than perfectly emulate any biological model per se. The ecology of creatures that were researched was more an inspiration into how a high population of units could potentially be managed rather than an end goal in and of itself.

to be reckoned with. But, rather than discuss how bacteria manage to infect and infest a host body, doing unimaginable damage to organisms incomparwwable to them in size, let us instead observe a more beneficial contract in which bacteria can enter with a host. An intriguing example of this is the mutualistic relationship of the Vibrio Fischeri bacterium and the Hawaiian Bobtail Squid. 4 In this relationship the squid will grow bacteria in its body because Vibrio Fischeri have bioluminescent properties. The way the squid uses this glowing ability is to replicate the moon’s light during nighttime while it is swimming on the ocean’s surface, rendering itself invisible to predators who are unable to distinguish between moonlight and the squid. In return the bacteria are well fed and protected by inhabiting the body of this marine cephalopod. The question though is – how do the bacteria know when there is enough of them together that their shine will be visible?

With that in mind, findings about these groups, which will range from pack mentality groups all the way to physiologically dependent colonial societies, are seen more as curiosities to be observed in relation to the system we are working on, so as to give overall insight into the goings-on of our own colonial creature(s). BACTERIA

…bacteria can talk to each other ... and what this chemical communication does is to allow bacteria to act as enormous multicellular organisms and accomplish tasks that they could never accomplish as individuals.3

The chemical language Bassler is referring to is based on releasing proteins into the environment and letting other bacteria pick them up. Once a suitable number has attached to a bacterium it will tentatively know that it is situated in a highly populated area, and perhaps it will start to glow. This coordination of activity displays a pack mentality of bacteria and their far-reaching sensory capabilities that help them organize and coordinate. While calling bacteria a social being might be an overstatement, their primitive communication and organization skills do quite successfully enable them to achieve an otherwise unattainable goal.

It is not hard to see why “safety in numbers” is a phrase commonly invoked when discussing predation and overall survival chances of individuals and groups in nature. This is especially true when your overall agency is not particularly significant and there is little doubt that when it comes to being a bacterium, regardless of your respective species, the general consensus is – you are hardly able do much alone.

The idea of low singular agency, but a potent group agency is certainly appealing when it comes to trying to conceptualize what exactly our system is trying to be. The advantages are clear since they display a clear economy of means on the level of the unit, but very complex effects on the level of a high-population aggregate.

While not very successful in isolation, the reason bacteria are surviving and thriving despite their small size is exactly because they are able to collaborate in enormous numbers in order to achieve their goals. Once their limited individual agency is multiplied over millions of cells, the lowly bacterium becomes a force toward the sun (phototropism) and by chemotaxis. vii. The ability to produce new individual organisms, either asexually from a single parent organism, or sexually from two parent organisms. 3 Bassler, B. (2010). iBiology Princeton: Bacterial Communication via Quorum Sensing. Available at: https://www.youtube.com/ watch?v=saWSxLU0ME8 (Accessed: July 17th, 2015). 4 Bassler, B. (2010). iBiology Princeton: Bacterial Communication via Quorum Sensing. Available at: https://www.youtube.com/ watch?v=saWSxLU0ME8 (Accessed: July 17th, 2015).

[Essays] However, as successful as they are, bacteria are still only exactly that – an aggregate. The pack mentality of the group does not truly enable them to communicate and collaborate meaningfully as a whole. This model is still based on accidental occupation of the same space at one point in time rather that active efforts towards creating a colony. This is where the biological model we explored next shows a higher level of complexity while retaining the overall effects observed in bacterial collaboration.

completely consumed by the colony is called eusociality. While the difference between social and eusocial may seem small at first, these two modes of cohabitation are completely different. Perhaps the easiest way to address these differences is to refer to one of the fundamental processes that can be observed in nature – competition. All forms on life on Earth participate in this daily struggle for survival and this struggled is fueled by “biological selfishness”. Competition will happen between different species, as well within the same one and even the same group of animals, be the subject in question a social one or not. It is the individuals who best look out for their own interests and the interests of their young that will survive the longest. This is where colonies of eusocial insects diverge so radically that even Darwin himself had the problem of incorporating them into his theory of evolution.

SOCIAL INSECTS

It was a grey, cool autumn day and all the bees were home, now agitated by the surgery. I finally plunged my hand into the mess of comb. Hot! Ninetyfive degrees at least. Overcrowded with 100,000 cold-blooded bees, the hive had become a warm-blooded organism.5

Individuals are faced with the problem of how to divide their energy between intercolony competition and intracolony competition - that is, within-group tugs-of-war over shares of resources gained through intergroup competition (between groups tugs-of-war) … when ecological and genetic factors advance a society to near the upper extreme of the superorganism continuum, subsequent selection may result in the complete loss of costly physiological structures involved in within-group competition.6

The reason why 100,000 cold-blooded insects could create a warm hive is a collaborative distributed behaviour that makes certain members of the colony go into “heater-mode”. By using bodily vibrations they are able to produce enough heat to warm the colony during cold days. What is of particular interest in the way Kelly addresses this encounter is the idea that the cold bodies of many have successfully coordinated their behaviour and managed to create a warm-blooded one. How does one logically start referring to a group of seemingly separate entities as one organism? Unlike the bacteria that were previously discussed, what is at play here is far more complex than habitual coordination inside a pack. Bee colonies are individuals in their own right because functionally, they start to structure their society in a way where every individual becomes interlinked and dependent on everyone else performing their respective duties. In biology this kind of dependency and connectedness where the individual is

This strange removal of physiological markers that drive inter-colony competition essentially results in a generation of a caste-based social colony of specialized individuals which has all but removed its “selfish” gene. Therefore, while selfishness is a valid survival strategy for so many solitary organisms (and many primitively “social” ones), by prioritizing the group over the unit that comprises it, collaboration gives rise to potentially beneficial behaviours that start delineating the colony as a different kind of an individual – a superoganism.7 The inner

5 Kelly, K. (1994). Out of control. Reading, Mass.: Addison-Wesley, p.9.

the traditional sense.

6 Holldobler, B. Wilson, E. and Nelson, M. (2009). The Superorganism: The Beauty, Elegance and Strangeness of Insect Societies. New York: W.W. Norton. p.44. 7 Biologically, there is a lot of dispute whether the superorganismic condition even warrants a category of its own. However, for our purposes we have adopted this moniker since there are some very interesting similarities and departures from the organismic behavior that were seen as desirable in defining what the system we are proposing does and how it exactly behaves since it evades biological definitions of an organism in

[Essays] workings of bee colonies therefore, have more in common with how your body functions as a whole with all its cells than they do with a pack of lions working together to catch an antelope.

of multiple units arranged into alternative physiologies that will essentially solve the division of labor through behavioral patterns enabled through communication. In this way the structural homogeneity amongst units is still seen as very preferable and attainable, while different task execution is solved through a communication model that employs a scalable number of units as performative aggregations. This is what leads us to the problem of medium scales in our system, but that is to be discussed later.

The reason why this mode of functioning is of any interest in the first place is the idea of side-stepping the usual problems that plague modularity in architecture. Once something is reduced to a replicable component, that component starts consuming the project in a way where any eventual arrangement of these multiples results in just that – a pile of many, unsuccessful at forming an overarching unity. Basic principles of eusociality, therefore, uncover the fundamental rules of the game when it comes to designing with multiples.

SUPERORGANISM: COMPUTE/ORGANIZE/ METABOLIZE AS SYNONYMS WITHIN THE BIODIGITAL PARADIGM

The central problem of life is the problem of how matter came to organize itself to produce autonomous, stable entities that are self-directing.9

However, there are aspects of eusociality that are in a way not desirable for the system that we are proposing. Inside eusocial societies such as the one explained above, the same physiological specialization that pushes a group into a higher form of sociality ultimately results in a group so dependent on the castes it has established, that no individual is able to function outside the group.

Technological systems become organized by commands from outside, as when human intentions lead to the building of structures or machines. But many natural systems become structured by their own internal processes: these are the self-organizing systems, and the emergence of order within them is a complex phenomenon that intrigues scientists from all disciplines.10

The key transition occurs at a point in colony evolution that can be conveniently called the “point of no return”. Beyond this level, it is impossible, or at least difficult and uncommon, for a species to regress from the eusocial to a more primitively eusocial, pre-social, or solitary condition.8

… “materiality” - the idea that a machine must be made of actual matter, of the hundred or so existing parts. This is wrong for examples can readily be given showing that what is essential is whether the system, of angels and ectoplasm if you please, behaves in a law-abiding way… A “machine” is that which behaves in a machine-like way, namely, that its internal state, and the state of its surroundings, defines uniquely the next state it will go to.11

Biologically, the mentioned “point of no return” marks a very significant shift in how a group becomes a fully-fledged and specialized eusocial colony. However, if it was to be replicated it would ultimately create a significant handicap in the proposed design system on the level of a unit. We hope to subvert this model of physiological specialization into one born of collaboration and communication. The “castes” in our system will be a byproduct 8 Wilson, E. and Holldobler, B. (2005). Eusociality: Origin and consequences. Proceedings of the National Academy of Sciences, 102(38), pp.13367-13371.

Principles of Self-Organization: Transactions of the University of Illinois Symposium, Robert Allerton Park, June 8-9, 1961. Emergent Publications. Available at: http://tinyurl.com/AshbyMachine (Accessed: July 15, 2015).

9 Kwinter, S. (2008). A Discourse on Method (For the Proper Conduct of Reason and the Search for Efficacity in Design). In Staub, U. and Geiser, R. (2008). Explorations in architecture. Basel: Birkhauser, p.37. 10 Yates, F., Garfinkel, A., Walter, D. and Yates, G. (1988). Self-Organizing Systems. Boston, MA: Springer US. 11 Ashby, W. R. (1962) ‘Principles of the self-organizing system’,

[Essays] By disembodying the machine and describing it through operational quality rather than its supposed corporeal faculties, Ashby claims that “without ambiguity or evasion, what we [today] mean by machine is – organization”. 12 This, as he calls it, “finite automaton” is described by its ability to compute/organize/metabolize its surroundings in relation to its internal logic in a way that produces constrained arrangements of a vastly bigger solution space of possible outcomes.

first step towards achieving organization, the units were abstracted to the level of simple communicational entities passing information about themselves between each other. We therefore started from a simple packing engine which attempts to distribute freely moving particles in an arrangement where no particle is in the “personal space” of any other one. In this example the information being passed around would be the minimum distance each particle can have to any other one in the system before it is given a vector that would redistribute it elsewhere. In an effort to motivate the system into further change we extended the number of variables that come into play. Therefore the information package was extended from a minimum distance; to also the number of respective neighbors any one particle has. In an effort to create reactionary agency in these particles outside their propensity towards packing, every inactive particle would have a chance to become an active based on their neighborhood. This active state of a particle is described through the change into an attractor which passes an attraction vector to every particle which is within its range. The actual condition under which a particle turns active (or inactive for that matter) is governed by specific rules based on neighborhoods14 which are then stored inside our machine along with the minimum distance needed to resolve a simple “packing” machine.

He describes this internal logic as a state of “if conditionality”, in which meaningful communication enables organization to occur. This is made possible by causality of change between constituent parts in a particularly constrained way, where one change in A results in a specific change in B. How then does a system eventually arrive to a point where it is appropriate to affix the “self” prefix to its organizational capabilities? According to Ashby it is only a matter of time and scale on which the event is observed.

...every isolated determinate dynamic system obeying unchanging laws will develop organisms that are adapted to their environments.13 Making the distinction between the “machinic” and “organic” clearly ceases to be relevant as was pointed out earlier [see p.40]. The previously observed biological systems certainly do use their own considerable computational abilities to achieve favorable patterns and arrangements when it comes to achieving goals. However, to start our own exploration in a computer-generated, self-organized system, instead of establishing clear biological goals necessary for survival like its living counterpart, we focused simply on creating a computational logic that successfully fulfills the basic criteria Ashby outlines in his writing as a “good” organization.

By deploying these rules within a population of particles, we started observing change expressed through global patterns caused by local interactions. Creating a reproducible pattern was essentially the first step in evaluating whether the system was successfully executing the rules that were implemented. The reason why this was important at all is because this would be the first attempt at even trying to computationally conceptualize selforganizational properties for our system.

Self-organization refers to a broad range of pattern-formation processes. In each case, however, a system of

Since establishing communication was the 12 Op. Cit.

of the square that is being checked and changing the checked square to either of the two states. This operation is executed iteratively and only ceases when the program is stopped or the whole system comes to a standstill where no further change is possible because the Stasis Rule (no change is being made to the current state) is met for every square in the grid.

13 Op. Cit. 14 This model is an adapted variation on the well-known generative engine of a cellular automaton. Cellular Automata (commonly known as CA) can best be described as a board of 9 squares arranged in a 3x3 grid. Every square in this grid is either “on” or “off”, and these two states are regulated by rules commonly referred to as “the game of life rules” (Stasis – no change, Loneliness – “off”, Reproduction –“on”, Overcrowding – “off”). These rules mandate change by counting the numbers of “on” and/or “off” squares in the immediate neighborhood

15 Camazine, S. (2001). Self-organization in biological systems. Princeton, N.J.: Princeton University Press, p.8.

[Essays]

living cells or organisms builds a pattern and succeeds in doing so with no external directing influence, such as a template in the environment or directions from a leader. Instead, the systemâ&#x20AC;&#x2122;s components interact to produce the pattern, and these interactions are based on local, not global, information.15

contraction once a certain number of units inside a local neighborhood are reached. The pulsing itself is achieved through activation of internal particles while an attractive membrane of surface actives promotes fusion of separately emerging pulsers. The ruleset for pulsing is two-fold. The first part of the ruleset addresses the peripheral neighborhoods stating that particles with less than 5 neighbors become attractors, which ensures that lonely particles and particles that exist on the very edge of the densely packed aggregation become active. This creates a tendency to group particles together so that even if the initial setup is dispersed initial aggregations will start emerging within seconds of the simulation being run. The second part of the simulation addresses the high density neighborhoods of particles (between 14 and 25 neighbors) that exist in the centroid of the pulsar. Most of these particles are logically located in central areas of aggregations because that is the only way that one could expect them to have high neighborhoods at all.

After many attempts into fine tuning the variables that came into play, the most prominent types of behavior that we observed were named Stringing and Pulsing. Stringing This communicational pattern produces a system in which units move through thin pathways radiating from the core of the population through the activation of peripheral units. It shows propensity towards a high level of distribution over time, but can also hold consistency quite successfully. Basically, the rules create conditions in which every particle that has less than 716 immediate neighbors becomes an attractor. The first phase of development can be described as a process by which all the particles start joining together in a solid aggregation with a high density. Once this phase is complete, since most particles now have more than 7 neighbors, the system comes to a stand-still. Slowly, only the particles on the absolute periphery are able to pass from their inactive into active state, and these peripheral units start forming the beginnings of a string. As time progresses, simple collisions these starting points will push out and start stringing along other particles from the original solid aggregation, creating a thin pathway. This action will continue until such time when the entire system is distributed into thin pathways, referred to as â&#x20AC;&#x153;stringsâ&#x20AC;?.

The ruleset states that these particles would become attractors, which introduces the internal flex or pulse and which is the inspiration for the name of this ruleset. However, once a neighborhood becomes too tightly packed, the particles return to their inactive states, ensuring that the pulsar will continue holding shape and flexing without being compressed into a single point.17 These tests were of interest because they enabled us to create a successful engine that resolves itself over time and achieves reproducible behaviors that can be isolated as more than simply a redundancy of the system or arbitrary functioning without a recognizable pattern. This ability to produce an observable behavioral pattern in the system was proof of the overall stability of our machine, albeit its functioning has yet to be practically applied to an explicit objective.

Pulsing In pulsing a communicational pattern produces a densely packed aggregation of units. It displays a stable internal metabolism of 16 It should be noted that the numbers of neighbors that factor in the ruleset are rarely highly specific. These values exist inside a domain where the exact number is prone to change in relation to the various other variables in the simulation (total particle population, bounds of the simulation space, density, distribution and the initial setup of the simulation).

Interestingly enough however, this tendency to explode, enabled pulsers to achieve more favorable configurations of units so that within seconds it could adjust itself to a smaller, but more stable pulser. Essentially, our packing system was still the primary driving mechanism for particle distribution, the only difference was that the conditions of the stable configuration were now being pushed by the appearance of attraction forces in the active particles.

17 In one of the earlier tests we recognized the importance of finetuning these values and deactivating particles with an exceptionally high neighbor count because the attractive force would compress a high number of particles into a small space, causing them to eventually explode away from that point once they reach a critical point.

[Essays]

SEEING THE FOREST FOR THE TREES Modularity in architecture has often been plagued by the eventual domination of the module in respect to what it actually builds. Overly designed modules begin dictating their higher-count arrangements, which might not be so worrisome had modularity not promised what it continuously fails to achieve once it falls victim to its overproduced module – variety and adaptability.

consequences to uncover root causes and direct it to studying overall global behavior of our system in order to ascertain what its synergic element (module) is. The idea is to extrapolate data from higher levels of structuring and organization and collect criteria that a module needs to meet. It will remain an abstracted unit of communication up until a point where technical questions about its design need to be asked in order to further inform the possible interactions it will have with other modules as a part of a wider technological problem and overall feasibility. Therefore, we engage higher levels of organization first, treating them as strange creatures inhabiting the proposed new world, in order to surmise what makes them tick.

Defining a module is a reductionist approach which is inherently a limiting process and while limitation is ultimately necessary, modularity often engages the process of limitation at too early of a stage in project development. The original conceptual problem of diversity achieved through various ways of structuring is usually supplanted by the question of technical feasibility of the module. It is not so much the question of whether the module should be problematized – or course it should, it is in many ways a somewhat inevitable method of rationalization; but the question is rather when one engages the module? We propose – the very last second.

With this in mind, we have established a semantic framework to help us define the levels of organization we anticipate will come into play and give them broad goals in terms of functioning and structuring. The superorganism: A high population of grippers, spheres and bodies.

The biological models that have been addressed as part of the initial research establish a framework that exploits the methods employed by scientists while studying multi-unit biological systems. Behavioral and social biology of animals is studied not only in respect to the individuals that comprise groups, but also the relationship of group behavior and how it affects and changes the individual. While scientists are ultimately searching for a truthful model of the world which exists in such a way that the theories used to explain it do not oppose or exclude each other, the end game of design is quite different. It is the eventual construction of a completely new reality which functions as a global mechanism of change that alters the world’s previous condition. Keeping this in mind we inherit the scientific pathos of studying

The body: A low population of grippers and spheres The species: A gripper and a sphere By reversing the process, we hope to address the objectives (and promises) of modularity by using an abstracted module to test behaviors, interactions and arrangements of a higher order. Only then can we limit the system through rationalization processes necessary for technical development of the module. The Performative Pieces and Aggregation Through a bottom-up communication process, analyzed with our abstracted module, we explore behaviour as a series of network of

[Essays] properties (similar to cellular interaction). This interaction, established within the design system, results in a highly performative complex piece mimicking details of formation and dynamic process of evolving forms. This collection of properties and its network consists of series of actions and switches that respond over the course of formation of the system. Each is both a response to its subsequent relationship to itself and a reaction to the condition of the system. The range of interaction, as a sum of group behaviour, determines an emergent outcome as a formal response from the system to its environment. It determines the relational whole that stems from specie to specie, specie to a body, body to superorganism and the superorganism to inhabited space.

target radius of influence; the most affected by the organizers are the closest ones. These organizers form various concentration gradients that determine the group behaviour. Specie Communication The species perform in unison. At a very basic level they have an on-off condition that either releases or stops, turns on or off, etc. The state in which they perform these switches and the stage of formation is what determines and conditions the variety of the aggregation allowing a dynamic and continuous response to the climatic region they are within. By responding to the biological nature of forming a network of properties and reversing the process of addressing typical modularity to determine the final design system, we wish to expand on the potentials of the system and its performative response to the conditions we have set out to explore. Focusing on understanding behaviour and communication and self-organization through specie-tospecie influence we hope to establish an understanding of a unifying metabolism that opens up new adaptive solutions to architecture.

Specie Behaviour Examining genetic machinery and the systemsâ&#x20AC;&#x2122; components of interaction, such as agents or modules, as they form and adapt themselves to their surrounding condition, it is possible to extrapolate a scaleless process of development of form as a study to gain an insight into the kind of bottom-up interaction that occurs between the agents. The modules or agents within the system behave in response to each other but also in a result to their interpretation of local condition. The organization can be likened to cell differentiation where specific modules are called out to exude an area of influence that allows for differentiation to occur. Specific modules will start to call themselves out, inhibit others from doing so and form regions that eventually establish a certain relational patterning. Organizers set out by the modules share property of influencing the formation of patterning through a shared and unifying metabolism by responding to the external factors they are delegating as well as having the control to inhibit other modules from responding, should it be necessary. Through a metabolic effect, the modules of organization influence the overall development by their

[Two Species]

GRIPPER AND SPHERES

[Two Species]

TWO SPECIES

GRIPPER AND SPHERE The sphere and the gripper are seen as two species. The primary goal of the gripper is defining connections, organizations and building up frameworks in the system, while the sphere is in charge of occupying and actuating these frameworks. The models and prototypes were pneumatically controlled and actuated silicone-casts.

[Two Species]

A TIME-BASED SYSTEM THAT IS EVER-CHANGING Non-Newtonian fluid provided a way to examine the morphing behaviour of a body. For more on bodies go to page 142.

[Two Species]

GRIPPER AND SPHERES The relationship between grippers and spheres is not finite. They each have specific behaviours and together form relational high level populations.

[Two Species]

LINEAR 01

LINEAR 02

LINEAR 03

LINEAR 04

LINEAR 05

LINEAR 06

LINEAR 07

LINEAR 15

LINEAR 16

LINEAR 17

LINEAR 18

LINEAR 19

LINEAR 20

LINEAR 21

LINEAR 29

LINEAR 30

3 LEG EVEN 01

3 LEG EVEN 02

3 LEG EVEN 03

3 LEG EVEN 04

3 LEG EVEN 05

3 LEG UNEVEN 07

3 LEG UNEVEN 08

3 LEG UNEVEN 09

3 LEG UNEVEN 10

3 LEG UNEVEN 11

3 LEG UNEVEN 12

4 LEG EVEN 01

4 LEG EVEN 09

4 LEG UNEVEN 01

4 LEG UNEVEN 02

4 LEG UNEVEN 03

4 LEG UNEVEN 04

5 LEG EVEN 01

5 LEG EVEN 02

TRIANGLE 01

TRIANGLE 02

TRIANGLE 03

TRIANGLE 04

OVAL 01

OVAL 02

OVAL 03

CIRCLE 04

CIRCLE 05

CIRCLE 06

CIRCLE 07

CIRCLE 08

CIRCLE 09

CIRCLE 10

SPHERE 04

SPHERE 05

SPHERE 06

SPHERE 07

TAXONOMY OF TWO SPECIES A taxonomy of all of the grippers and spheres we studied.

[Two Species]

LINEAR 08

LINEAR 09

LINEAR 10

LINEAR 11

LINEAR 12

LINEAR 13

LINEAR 14

LINEAR 22

LINEAR 23

LINEAR 24

LINEAR 25

LINEAR 26

LINEAR 27

LINEAR 28

3 LEG EVEN 06

3 LEG UNEVEN 01

3 LEG UNEVEN 02

3 LEG UNEVEN 03

3 LEG UNEVEN 04

3 LEG UNEVEN 05

3 LEG UNEVEN 06

4 LEG EVEN 02

4 LEG EVEN 03

4 LEG EVEN 04

4 LEG EVEN 05

4 LEG EVEN 06

4 LEG EVEN 07

4 LEG EVEN 08

5 LEG EVEN 03

5 LEG EVEN 04

5 LEG EVEN 05

5 LEG EVEN 06

5 LEG EVEN 07

8 LEG EVEN 01

8 LEG EVEN 02

OVAL 04

OVAL 05

OVAL 06

OVAL 07

CIRCLE 01

CIRCLE 02

CIRCLE 03

CIRCLE 11

CIRCLE 12

CIRCLE 13

CIRCLE 14

SPHERE 01

SPHERE 02

SPHERE 03

SPHERE 08

SPHERE 09

SPHERE 10

BENDING

BALLOONING

[Two Species]

CATEGORIZING THE BODIES The main goal of a singular species is mobility, therefore we categorized the models based on movements, gestures and the ability to stand, walk or roll.

[Two Species]

TWISTING

STANDING + WALKING

ROLLING

[Two Species]

EARLY MODELS A variety of some of our first linear, gripper, circular and spherical species.

[Two Species]

[Two Species: Gripper]

THE GRIPPER

[Two Species: Gripper]

THE GRIPPER The primary goal of the gripper is defining the connection, organization and building up frameworks in the system. Grippers are radial members that use their extremities to move and connect to one another. At a singular level their goal is mobility. As a gripper communicates with other grippers their communal goal is to organize and interface the system. Grippers are in charge of building up frameworks that the spheres can occupy and actuate.

[Two Species: Gripper]

LINEAR 01

LINEAR 02

LINEAR 03

LINEAR 04

LINEAR 05

LINEAR 06

LINEAR 07

General Description: Linear divisions Cast: No Inflated Description: NA

General Description: Angled divisions Cast: No Inflated Description: NA

General Description: Three small pockets Cast: No Inflated Description: NA

General Description: Nine large pockets Cast: No Inflated Description: NA

General Description: Three larger pockets Cast: Yes Inflated Description: Ballooning

General Description: Twenty-five small pockets Cast: Yes Inflated Description: Ballooning

General Description: Five trees 1 Cast: Yes Inflated Description: Did not work

LINEAR 15

LINEAR 16

LINEAR 17

LINEAR 18

LINEAR 19

LINEAR 20

LINEAR 21

General Description: Connected cells narrow Cast: Yes Inflated Description: Bending

General Description: Connected cells separated Cast: No Inflated Description: NA

General Description: Connected cells jagged Cast: Yes Inflated Description: Did not work

General Description: Connected cells three separated into three Cast: Yes Inflated Description: Did not work

General Description: Gradient spacing air path to center and curved ends Cast: Yes Inflated Description: Bending at center

General Description: Gradient air path to end and curved ends Cast: Yes Inflated Description: Bending then curling at end

General Description: Gradient spacing air path to beginning and curved ends Cast: Yes Inflated Description: Bending then curling at beginning

LINEAR 29

LINEAR 30

3 LEG EVEN 01

3 LEG EVEN 02

3 LEG EVEN 03

3 LEG EVEN 04

3 LEG EVEN 05

General Description: Three air paths with even spacing air path Cast: Yes Inflated Description: Bending in sections, solid silicone parts act as joints.

General Description: Four air paths with even spacing air path Cast: No Inflated Description: NA

General Description: Even air paths with a small pocket in the center Cast: Yes Inflated Description: All legs curl and grip onto things easily.

General Description: Even air paths Cast: Yes Inflated Description: All legs curl onto themselves.

General Description: Switch-back air paths in each leg Cast: Yes Inflated Description: Air paths expand legs horizontally rather than ballooning up.

General Description: Switch-back air paths with solid silicone at last 1/3 of leg Cast: Yes Inflated Description: Solid tip provides more stability for the gripper to lift off the ground.

General Description: Switch-back air paths with separate air paths at last 1/4 of leg Cast: Yes Inflated Description: Variety in inflation allows for more varied movement.

3 LEG UNEVEN 07

3 LEG UNEVEN 08

3 LEG UNEVEN 09

3 LEG UNEVEN 10

3 LEG UNEVEN 11

3 LEG UNEVEN 12

4 LEG EVEN 01

General Description: Connected cells narrow Cast: No Inflated Description: NA

General Description: Even air paths Cast: Yes Inflated Description: First multi-legged “walker”, the front two legs inflated and stabilized while the back leg pushed the body forward.

General Description: Even air paths Cast: Yes Inflated Description: Walker. Silicone was tacky, which limited it’s ability to move. We added a “hairy” skin and Styrofoam balls to the bottom to help reduce friction.

General Description: Even air paths with separate inflation points Cast: Yes Inflated Description: Solid tip provides more stability for the gripper to lift off the ground.

General Description: Ball pockets Cast: Yes Inflated Description: “Balls” inflate but don’t act in the same way the Styrofoam balls do in that they still create too much friction.

General Description: Switch-back air paths with separate air paths at last 1/4 of leg Cast: Yes Inflated Description: Variety in inflation allows for more varied movement.

General Description: Linear divisions Cast: Yes Inflated Description: Ballooning

4 LEG EVEN 09

4 LEG UNEVEN 01

4 LEG UNEVEN 02

4 LEG UNEVEN 03

4 LEG UNEVEN 04

5 LEG EVEN 01

5 LEG EVEN 02

General Description: Switch-back air paths with separate air paths at last 1/4 of leg and central air path Cast: Yes Inflated Description: Central air path allow gripper to pick it’s body up off the ground.

General Description: Connected cells narrow Cast: Yes Inflated Description: Did not work

General Description: Even air paths Cast: Yes Inflated Description: Body lifts off the ground evenly and smoothly.

General Description: Even air paths with separate inflation points Cast: No Inflated Description: NA

General Description: Switch-back air paths and “hairy” center Cast: Yes Inflated Description: Bending is very even. Pointed legs don’t provide enough stability for body causing it to tip over.

General Description: Even air paths Cast: Yes Inflated Description: All legs curl onto themselves.

General Description: Even air paths Cast: Yes Inflated Description: All legs curl smoothly.

GRIPPER TAXONOMY The gripper taxonomy includes and exploration of linear elements, which can be seen as studies of a grippers’ individual leg.

[Two Species: Gripper]

LINEAR 08

LINEAR 09

LINEAR 10

LINEAR 11

LINEAR 12

LINEAR 13

LINEAR 14

General Description: Five trees 2 Cast: Yes Inflated Description: Did not work

General Description: Five trees 3 Cast: Yes Inflated Description: Did not work

General Description: Five trees 4 Cast: Yes Inflated Description: Did not work

General Description: Five trees 6 Cast: Yes Inflated Description: Did not work

General Description: Five trees 7 Cast: Yes Inflated Description: Did not work

General Description: Connected cells narrow Cast: Yes Inflated Description: Bending

General Description: Connected cells wide Cast: Yes Inflated Description: Bending

LINEAR 22

LINEAR 23

LINEAR 24

LINEAR 25

LINEAR 26

LINEAR 27

LINEAR 28

General Description: Angled shape air path to end and curved ends Cast: Yes Inflated Description: Bending then curling at end

General Description: Angled shape air path to beginning and curved ends Cast: Yes Inflated Description: Bending then curling at beginning

General Description: Gradient spacing air path to center and flat ends Cast: Yes Inflated Description: Walking... flat ends help stabilize the body... continue to use

General Description: 5cm length with even spacing air path Cast: Yes Inflated Description: Curls and tips over

General Description: 10cm length with even spacing air path Cast: Yes Inflated Description: Curls and tips over

General Description: 15cm length with even spacing air path Cast: Yes Inflated Description: Curls into a coil and tips over

General Description: 20cm length with even spacing air path Cast: Yes Inflated Description: Curls into a coil and tips over

3 LEG EVEN 06

3 LEG UNEVEN 01

3 LEG UNEVEN 02

3 LEG UNEVEN 03

3 LEG UNEVEN 04

3 LEG UNEVEN 05

3 LEG UNEVEN 06

General Description: Three linear divisions Cast: No Inflated Description: NA

General Description: Many linear divisions Cast: No Inflated Description: NA

General Description: First try at connected air paths Cast: Yes Inflated Description: Balloons and slightly bends

General Description: Connected cells narrow Cast: No Inflated Description: NA

General Description: Connected cells narrow Cast: Yes Inflated Description: Did not work

4 LEG EVEN 02

4 LEG EVEN 03

4 LEG EVEN 04

4 LEG EVEN 05

4 LEG EVEN 06

4 LEG EVEN 07

4 LEG EVEN 08

General Description: Variation of gradient spacing and angled shape air paths Cast: Yes Inflated Description: Bending

General Description: Even spaced air paths Cast: Yes Inflated Description: Even bending that leads to gestures

General Description: Evenly spaced air paths and flat ends Cast: Yes Inflated Description: Gesturing... flat ends help stabilize the body

General Description: Long, thin legs with evenly spaced air paths Cast: No Inflated Description: NA

General Description: Even air paths Cast: Yes Inflated Description: All legs curl onto themselves

General Description: Switch-back air paths at slightly webbed at interior corners and solid tips Cast: Yes Inflated Description: Solid tip provides more stability for the gripper to lift off the ground

General Description: Switch-back air paths with separate air paths at last 1/4 of leg Cast: Yes Inflated Description: Variety in inflation allows for more varied movement

5 LEG EVEN 03

5 LEG EVEN 04

5 LEG EVEN 05

5 LEG EVEN 06

5 LEG EVEN 07

8 LEG EVEN 01

8 LEG EVEN 02

General Description: Switch-back air paths with three separate air paths per leg Cast: Yes Inflated Description: Variety in inflation allows for more varied movement.

General Description: Three straight air paths per leg with ridging at tips Cast: Yes Inflated Description: Leg movement is uncontrollable but animated

General Description: Linear divisions Cast: No Inflated Description: NA

[Two Species: Gripper]

S-bend leg

Curving Leg

3D twisting leg

Standing four-leg gripper

Curling four-leg gripper

Four-leg gripper holding on

Three-leg gripper grabbing a finger

Walking three-leg gripper (in process)

Walking three-leg gripper

Three-leg gripper with individually actuated legs

Scooting four-leg gripper

Curling four-leg gripper

Five-leg gripper with individually actuated legs

Five-leg gripper with inflated tips

LEGS AND GRIPPERS A sneak peak of whatâ&#x20AC;&#x2122;s to come.

[Two Species: Gripper]

A GRIPPER

[Two Species: Gripper]

MATERIAL: SILICONE We used silicone as a material to create the grippers, which have interior ridging to control inflation and movement (shown in their un-inflated states).

[Two Species: Gripper]

NEUTRAL

INFLATED

SILICONE ANALYSIS

A THIN LAYER OF SILICONE BREAKS EASILY

A THICK LAYER OF SILICONE RESTRICTS EXPANSION

EVEN SILICONE = EVEN EXPANSION

TIGHT RIDGING

NOT EFFICIENT AIR DISTRIBUTION

GRADIENT SPACING

EVEN SPACING - REGULAR DISPERSION

IRREGULAR RESULTS

CONTROLLED EXPANSION

MATERIAL: DETAILS Material parameters of the silicone.

[Two Species: Gripper]

3 LEG EVEN 02 SKIN

3 LEG EVEN 05 SKIN

3 LEG EVEN 06 SKIN

General Description: Three even rows of hair per leg Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

General Description: Gradient pattern of circles, square and pentagons Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

3 LEG UNEVEN 09 SKIN

4 LEG EVEN 06 SKIN

5 LEG EVEN 04 SKIN

General Description: Three even rows of hair per leg Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

General Description: Three even rows of hair per inflation area Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

4 LEG UNEVEN 04 SKIN

5 LEG EVEN 01 SKIN

5 LEG EVEN 04 SKIN

General Description: Very fine hair Cast: Yes Inflated Description: Helps reduce friction when gripper is walking, but not more so than the “regular” hair.

General Description: Three even rows of hair per leg Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

General Description: Three even rows of hair per inflation area Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

4 LEG EVEN 09 SKIN General Description: Gradient pattern of circles, square and pentagons Cast: Yes Inflated Description: Helps reduce friction when gripper is walking.

GRIPPER SKIN A hair-like micro-texture covers the bottom side of the gripper. This allows for greater mobility by lessening its friction on a surface and greater easy of entanglement with other grippers when they connect.

[Two Species: Gripper]

GRIPPER SKIN Hair-like skin (above). A fingerprint-like micro-texture covers the top side of the gripper (below). This pattern also helps to lessen friction on adjacent surfaces.

[Two Species: Gripper]

GRIPPER SKIN A fingerprint-like micro-texture covers the top side of the gripper. This pattern also helps to lessen friction on adjacent surfaces.

[Two Species: Gripper]

GESTURES AND MOVEMENTS While the primary goal of the gripper is mobility, we first had to understand gestures and movements the gripper could make.

[Two Species: Gripper]

[Growth Strategy]

GESTURES AND MOVEMENTS Gestures and movements explored in physical prototyping.

[Two Species: Gripper]

sequential inflation of the chambers induces a wiggle

MOBILITY: SINGLE LEG Triple chamber unattached limbs liberated multi directional bending in one limb which was before constrained to one axis of movement.

[Two Species: Gripper]

MOBILITY: STANDING Above: An early silicone model is cast unevenly creating wobbly movement. Below: One of the last silicone models has a nearly perfect cast which allows for smooth movement when it is inflated.

[Two Species: Gripper]

MOBILITY: STANDING In the “perfect” world of simulations the actuation of movement is evenly distributed between the four “legs”. The bottom surface of the spheres are constrained, which is a direct derivative from the material properties of the physical model.

[Two Species: Gripper]

MOBILITY: WALKING OR ROLLING The gripper can get around using two methods: walking.(shown above) or roiling (shown opposite). In physical models we focused on proving the former.

[Two Species: Gripper]

MOBILITY We tested multiple air insert points in each leg to assist in control of mobility.

[Two Species: Gripper]

MOBILITY Styrofoam balls were added to the models to help lessen friction, but also provided joints and control points that allowed for more precise movement.

[Two Species: Gripper]

GRIPPER MOBILITY An uneven 3-leg gripper picks itself up and inches along.

[Two Species: Gripper]

GRIPPER MOBILITY An uneven 3-leg gripper picks itself up and inches along.

[Two Species: Gripper]

MECHANICAL ACTUATION OF MOVEMENT We controled the sequence of actuation using arduino-programmed valves and compressors.

100

[Two Species: Gripper]

101

[Two Species: Gripper]

MECHANICAL ACTUATION OF MOVEMENT We controled the sequence of actuation using arduino-programmed valves and compressors.

102

[Two Species: Gripper]

MECHANICAL ACTUATION: MOBILITY We controled the sequence of actuation using arduino-programmed valves and compressors.

103

[Two Species: Gripper]

30 cm radiu

1:1 SCALE GRIPPER Although the scale of the system is relation and based on population sizes, we determine the physical scale of the gripper based on our material research. We determined the full scale of gripper to have a 30cm radius (measured from the center to tip of leg).

104

[Two Species: Gripper]

1mm2 hair, high density 1mm2 hair, medium density 1mm2 hair, low density

inlaid magnets 3mm ø, typ concentric circle skin

interior ribbing, switchback pattern, typ solid joint to help control leg motion/movement air insert point, typ “fingerprint” skin

inlaid magnets 3mm ø inlaid magnets 10mm ø inlaid magnets 12mm ø

105

[Two Species: Gripper]

106

[Two Species: Gripper]

107

[Two Species: Sphere]

THE SPHERE

108

[Two Species: Sphere]

THE SPHERE The sphere is a passive unit whose motivation is to regulate the system. At a singular level the sphere’s only goal is mobility. It jams its body for structuring, inflates its body for infill, and inflates / deflates its exterior pockets for mobility. The fist prototypes of a sphere were an exploration into the mobility of the unit through an adopted geometrical setup of a dodecahedron where its cells could be separately inflated. Digital simulation, abstracting the behaviour of the physical prototype, showcased the more controlled locomotion of the sphere in order to achieve directionality. The sphere has basic communication agency to seek grippers. Spheres are “listener” units that communicate with grippers but never each other. Grippers “call” spheres to a seeding location to grow a stalk, which is the beginning of a high population ecology.

109

[Two Species: Sphere]

TRIANGLE 01

TRIANGLE 02

TRIANGLE 03

TRIANGLE 04

OVAL 01

OVAL 02

OVAL 03

General Description: Three even divisions Cast: No Inflated Description: NA

General Description: Center/edge pocket Cast: No Inflated Description: NA

General Description: Directional ridging, top pocket Cast: No Inflated Description: NA

General Description: Four pockets Cast: Yes Inflated Description: Ballooning

General Description: Oval divided in half Cast: No Inflated Description: NA

General Description: Oval divided in quarters Cast: No Inflated Description: NA

General Description: Oval divided in six pockets Cast: No Inflated Description: NA

OVAL 04

OVAL 05

OVAL 06

OVAL 07

CIRCLE 01

CIRCLE 02

CIRCLE 03

General Description: Linear divisions Cast: No Inflated Description: NA

General Description: Symmetrical hourglass shape with center/ edge pocket Cast: No Inflated Description: NA

General Description: Symmetrical hourglass shape with two pockets large pockets and two small pockets Cast: No Inflated Description: NA

General Description: Symmetrical hourglass shape with linear divisions and two pockets Cast: No Inflated Description: NA

General Description: Four even divisions Cast: No Inflated Description: NA

General Description: Cross shaped division Cast: Yes Inflated Description: Balloons

General Description: Curved fan strips Cast: Yes Inflated Description: Balloons unevenly and moves slightly

CIRCLE 04

CIRCLE 05

CIRCLE 06

CIRCLE 07

CIRCLE 08

CIRCLE 09

CIRCLE 10

General Description: One pocket, solid ball as counter weight Cast: Yes Inflated Description: Ballooning

General Description: One pocket Cast: No Inflated Description: NA

General Description: Nine small pockets in one large solid circle silicone Cast: No Inflated Description: NA

General Description: Six cell circle Cast: No Inflated Description: NA

General Description: Nine cell circle Cast: Yes Inflated Description: Each cell balloons slightly.

General Description: Three touching cells with three pockets Cast: No Inflated Description: NA

General Description: Three touching cells with four pockets and shared air paths Cast: No Inflated Description: NA

CIRCLE 11

CIRCLE 12

CIRCLE 13

CIRCLE 14

SPHERE 01

SPHERE 02

SPHERE 03

General Description: Three touching cells with four pockets and shared air paths Cast: No Inflated Description: NA

General Description: Three slightly connected cells with three pockets Cast: Yes Inflated Description: Each cell balloons.

General Description: Three slightly connected cells with four pockets and shared air paths Cast: Yes Inflated Description: Each cell balloons.

General Description: Three slightly connected cells with four pockets and shared air paths Cast: Yes Inflated Description: The top cell doesn’t expand, the bottom cells balloon.

General Description: 4cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: 3.5cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: 3cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

SPHERE 04

SPHERE 05

SPHERE 06

SPHERE 07

SPHERE 08

SPHERE 09

SPHERE 10

General Description: 2.5cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: 2cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: 2.5cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: 2cm Ø Circular pocket Cast: Yes Inflated Description: Balloons into a sphere

General Description: Dodecahedron with balloon inflated faces Cast: Yes Inflated Description: Moves, but tube connection to tube is bad.

General Description: Dodecahedron with silicone inflated faces Cast: Yes Inflated Description: Moves well.

General Description: Dodecahedron w/ silicone inflated faces, interior aggregate and light Cast: Yes Inflated Description: Inflates. Light is blocked when sphere is jammed.

SPHERE TAXONOMY The sphere taxonomy includes and exploration of triangle, ovals and circles.

110

[Two Species: Sphere]

Hydrogel filled sphere experiment

Partitioned skin experiment

Circle 03

Circle 04

Inside/outside thoughts

Connection thought

Triangle 04

Circle 14

Sphere experiment

Dodecahedron sphere

Partitioned skin experiment

Skin hair experiment

Sphere covered in Styrofoam test

Sphere 08

Sphere 09

SPHERES A sneak peak of whatâ&#x20AC;&#x2122;s to come.

111

[Two Species: Sphere]

FIRST EXPERIMENTS Representational models of the sphere.

112

[Two Species: Sphere]

FIRST EXPERIMENTS Early circle models show ballooning. Left: start state, Right: inflated state

113

[Two Species: Sphere]

JAMMED Jamming introduces rigidity into the system.

NEUTRAL The sphere is passive in this state.

INFLATED Inflation introduces deformation in the system s the neighboring spheres collide

SPHERE STRUCTURING A sphere moves through a gradient of three states: inflated, neutral and jammed.

114

[Two Species: Sphere]

SPHERE PACKING Spheres will be packed within the net of grippers. Because we are working with spheres that inflate and deflate the sphere packing will be consistently irregular.

115

[Two Species: Sphere]

5mm

10mm

15mm

20mm

25mm

30mm

35mm

40mm

INFLATED The size of the sphere was explored to understand the relationship of proportion next to the gripper.

116

2sec, 35mm 6sec, 70mm

15sec, 125mm

18sec, 1350mm

9sec, 80mm

12sec, 100mm

3sec, 50mm

1sec, 20mm

[Two Species: Sphere]

INFLATED A single sphere that starts at 20mm in diameter grows to be over six times its size in 18 seconds with a constant pressure of 7PSI.

117

[Two Species: Sphere]

JAMMING Jamming was used to examine the ability of one object to grip onto another. Above are the steps , which occur over a about 5 seconds.

118

[Two Species: Sphere]

JAMMING Jamming was used to examine the ability of one object to grip onto another. Above are the steps , which occur over a about 5 seconds.

119

[Two Species: Sphere]

SKIN AS PASSIVE CONNECTION METHOD While there is no clear connection method between spheres, our intial intent was to use the stickiness of the silicone itself, allowing sphere interfacing to become a friction based model.

120

[Two Species: Sphere]

EVEN SQUARE1 Pattern Size: 2.25mm Sticks to Other Square1 When Deflated Sticks to Other Square1 When Inflated

EVEN SQUARE2 Pattern Size: 1.5mm Sticks to Other Square2 When Deflated Sticks to Other Square2 When Inflated

STAGGARED SQUARE1 Pattern Size: 2.25mm Sticks to Other Staggared Square1 When Deflated Sticks to Other Staggared Square1 When Inflated

STAGGARED SQUARE2 Pattern Size: 1.5mm Sticks to Other Staggared Square2 When Deflated Sticks to Other Staggared Square2 When Inflated

CIRCLE1 Pattern Size: 3mm Sticks to Other Circle1 When Deflated Sticks to Other Circle1 When Inflated

CIRCLE2 Pattern Size: 2mm Sticks to Other Circle2 When Deflated Sticks to Other Circle2 When Inflated

RHOMBUS1 Pattern Size: 2.5mm Sticks to Other Rhombus1 When Deflated Sticks to Other Rhombus1 When Inflated

RHOMBUS2 Pattern Size: 1.7mm Sticks to Other Rhombus2 When Deflated Sticks to Other Rhombus2 When Inflated

MICROTEXTURES Surface treatment of the sphere’s skin therefore became an extension of that idea, with microtexturing becoming a way to increase the contact area of the spehres’ skins.

121

[Two Species: Sphere]

DIGITAL SIMULATION OF INFLATION OF THE SPHERE Choreography of inflation in simulation provided a way to study potential movements in physical models.

122

[Two Species: Sphere] INFLATE TOP introduce tilt

DEFLATE UNDER deflate the underside to encourage roll

INFLATE BACK-ADJACENT push further out

INERTIA wait for full tilt

NEUTRAL new cycle

FULL ROLL one complete revolution

start

inflate a hinge 4 9 3 Right

inflate bottom

create instability

3 . 2 . 6 9 12 Forward & Left

3.9 6 1 Back

MOBILITY THROUGH INFLATION Mobility, which is the end goal, is achieved through choreography of pockets in the sphere.

123

end

[Two Species: Sphere]

MOBILITY The first prototype of a sphere was an exploration into the mobility of the unit adopting a basic geometrical setup of a dodecahedron where its cells could be separately inflated.

124

[Two Species: Sphere]

MOBILITY The first prototype of a sphere was an exploration into the mobility of the unit adopting a basic geometrical setup of a dodecahedron where its cells could be separately inflated.

125

[Two Species: Sphere]

MOBILITY In the second prototype the cells have sufficient rigidiy to test mobility in a controlled way through inflation, so we can see our first successful attempt in controlling its movement.

126

[Two Species: Sphere]

white JAMMED

grey RELAXED

COMPUTATIONALLY CONTROLLED BEHAVIOR

ROLLING FORWARD

ROLLING AND TURNING

CIRCLING

MOBILITY Locomotion is achieved through simulated inflation/jamming of compartments in its skin which offset its position through tilting, thereby steering the sphere.

127

black INFLATED

[Two Species: Sphere]

128

[Two Species: Sphere]

MOBILITY Spheres move through an inflated choreography of 12 individually actuatable faces surrounding itâ&#x20AC;&#x2122;s body..

129

[Two Species: Sphere]

THE SPHERE The sphere has a goal of occupying and actuating frameworks created by the grippers.

130

[Two Species: Sphere]

131

[Single Specie Communication]

SINGLE SPECIE COMMUNICATION

132

[Single Specie Communication]

SINGLE SPECIE COMMUNICATION Because we eventually wanted to see the species talking to each other, the next step was to address the problems behind interaction of both inter-species and cross-species communication. The first attempt at speculating that materially, was experimenting with silicone colouring as a way to index the inflation visually where the skinâ&#x20AC;&#x2122;s stretch changes the lightness of the color. This change is easily indexed by RGB sensors, making other around that unit understand whether inflation is going on or not. The bend sensor studies were more concerned with the gripper having a sense of its own limbs in order to know what the remaing limbs should be doing.

133

[Single Specie Communication]

223.50.55 fully deflated

indexing inflation

inflation information exchange

RGB sensor (reading color)

221.190.189 fully inflated

COMMUNICATION: GRIPPER The first method of address communication in grippers was experimenting with silicone colouring as a way to index the inflation visually. Where the skin stretches it changes the lightness of the color in that area.

134

[Single Specie Communication]

COMMUNICATION: GRIPPER The change in color of silicone is easily indexed by RGB sensors, making other grippers around able to understand whether inflation is going on or not.

135

[Single Specie Communication]

COMMUNICATION: SPHERE The sphere has an internal LED that is always on and acts as a way for the gripper to identify it.

136

[Single Specie Communication]

COMMUNICATION: SPHERE The sphere has an internal LED that is always on and acts as a way for the gripper to identify it.

137

[Body Plan Formation]

EXPERIMENT IN BODY PLAN FORMATION

138

[Body Plan Formation]

BODY PLAN FORMATION Bodies are the results of a temporary collaborative action of multiple grippers and cells that come together extending their movement abilities. At this level of organization in the system the primary concern was addressing the strategies of body formations. Thinking about grouping led to the consideration of the relationship of the two species to each other and how their response and deployment would affect the overall system. Once they are grouped together, grippers and spheres begin their symbiotic relationship that enables the system to begin structuring. Various body plans are the product of this grippersphere relationship. These body plans are treated as a unified whole performing as one. The physical prototypes of casted silicone species were made and used to study and research the material quality of the potentials of connecting possibilities. The grippers form various grids and nets that can contract, expand, curl and shift, while its counterpart sphere is deployed fluidly in the hands of the grippers forming a continuous and consistent metabolism for the overall body. The first study explored the various viable connections of the gripper including curling around others limbs as well s using magnetic connections which gripper limbs could actively seek out in order to connect to others. The array of documented movements defined multiple ways for the formation of this net such as twisting, curling, face to face with magnets embedded into the skin or overlapping of multiple positions creating an almost infinite amount of connective points. Spheres, due to its simple geometry, do not have a way of connecting to other spheres and instead enforces its relationship to the grippers ability to hold them together. Once this relationship and techniques were established, groups of various formations can be formed in a number of ways where grippers seek each other out and are propped up together in various ways by the spheres. This leads to a number of groups that can actuate as one body formation.

139

[Body Plan Formation]

THE START OF A BODY A body begins to form when a neighborhood of a few grippers and a few more spheres form..

140

[Body Plan Formation]

141

[Body Plan Formation]

THE START OF A BODY The relationship of the gripper and sphere is formed when the gripper holds onto one or many spheres.

142

[Body Plan Formation]

143

[Body Plan Formation]

PICKING UP SPHERES The grippers wrap around spheres - either in a one-to-one relationship, as seen here or one-to-many. The quantity of spheres to grippers is not finite.

144

[Body Plan Formation]

PICKING UP SPHERES The grippers wrap around spheres - either in a one-to-one relationship, as seen here or one-to-many. The quantity of spheres to grippers is not finite.

145

[Body Plan Formation]

Abstracted grippers forming a net

Body with variable number of spheres

Body showing inflation/jamming

Body mobility

Body with variable number of spheres

BODY A sneak peak of bodies to come.

146

[Body Plan Formation]

BODY Here a gripper holds four spheres.

147

[Body Plan Formation]

CONNECTIONS In order for a body to form grippers form a net. There are many connection types between grippers: entanglement, intertwining, and use of magnets. These are our first models of those nets with abstracted varieties of connections.

148

[Body Plan Formation]

149

[Body Plan Formation]

CONNECTIONS: ENTANGLEMENT In order for a body to form grippers form a net. There are many connection types between grippers: entanglement, intertwining, and use of magnets.

150

[Body Plan Formation]

CONNECTIONS: ENTANGLEMENT This inexact model of connection allows for a bigger margin of error and more possible arrangements of connecting limbs

151

[Body Plan Formation]

all open legs (soft/ deflated)

2 open legs (connection 1, soft/deflated) 1 closed leg (stiff/inflate)

1 open leg (connection 1, soft/deflated) 2 closed legs (stiff/inflate)

all closed legs (connection 1, stiff/inflate)

+ x1

units remain soft and stretchy

+ x1

CONNECTIONS: INTERTWINING Intertwining at the tip allows for stiffness at the connection and flexibility/stretchiness in the rest of the body or system.

152

[Body Plan Formation]

2 open legs (soft/deflated) 1 closed leg (connection 2, stiff/inflate)

1 open leg (soft/deflated 2 closed legs (connection 2, stiff/inflate)

2 closed legs (connection 1, stiff/inflate) 1 closed leg (connection 2, stiff inflate)

1 closed leg (connection 1, stiff/inflate) 2 closed legs (connection 2, stiff inflate)

all closed legs (connection 2, stiff/inflate)

+ x1

units become stiffer as more legs connect

+ x2

+ x1

CONNECTIONS: INTERTWINING Each limb has a particular state (curled and extended) so based on which two states the connecting limbs have, the connection can be more loose (extended+curled) or rigid (curled+curled).

153

[Body Plan Formation]

CONNECTIONS: INTERTWINING Slowly by attaching at the limb grippers start forming nets for envelopment.

154

[Body Plan Formation]

Wrapping

Face to Face

Overlapping

CONNECTIONS: INTERTWINING Depending on the relative position of one gripper to another the intertwining connections can be divided into groups pictured above

155

[Body Plan Formation]

CONNECTIONS: MAGNETIC Use of magnets further affects the overall stability of the connection, reinforcing the grip limbs have on each other.

156

[Body Plan Formation]

CONNECTIONS: MAGNETIC Similarly, embedded in the skin itself, magnets on the top skin layer of the gripper allow fot connections and reinforcements across the entire area of the skin.

157

[Body Plan Formation]

CONNECTIONS: MAGNETIC Exmaple where the magnetic connection is the main mode of connection.

158

[Body Plan Formation]

CONNECTIONS: MAGNETIC Properly distributed patterns of magnets with respect to polarity create connection points on the limbs.

159

[Body Plan Formation]

FORMATION OF A BODY The first level of organization in the system happens when grippers and spheres merge together to make a body.

160

[Body Plan Formation]

THE BODY An example of a formed body.

161

[Body Plan Formation]

DOWN

BODY FORMATION The formation of the body is the process of envelopment of spheres by the grippers.

162

[Body Plan Formation]

BODY FORMATION Grippers corralling the spheres.

163

[Body Plan Formation]

BODY FORMATION The sphere to gripper arrangement requires a collaboration between the two species with a goal of creating an enclosed unit.

164

[Body Plan Formation]

BODY FORMATION Spheres need to join together to create a body. Here the grippers are implied, because we did not yet know how the spheres become encased by the grippers.

165

[Body Plan Formation]

BODY FORMATION Grippers and spheres become a body.

166

[Body Plan Formation]

167

[Body Plan Formation]

MORPHING BODY A body is not a finite grouping. Above is an early exploration of the morphing of a body.

168

[Body Plan Formation]

MORPHING BODY In this model the number of spheres 20 grippers can contain is anywhere from 1 to 8. This is just one of many scenarios.

169

[Body Plan Formation]

BODY MOBILITY Once a body is formed it has various goals, one of which is mobility.

170

[Body Plan Formation]

BODY MOBILITY Once a body is formed it has various goals, one of which is mobility.

171

[Body Plan Formation]

MERGING TWO UNITS Two merging units release two free grippers. Those two grippers then join to create a new body.

172

[Body Plan Formation]

173

[Structuring]

LOW POPULATION FORMATION

174

[Structuring]

STRUCTURING What is particularly beneficial and significant about the relationship between the grippers and spheres is the latent property of the sphere once it is activated in groups with grippers. The ability of the sphere to jam enables it to go from inflated and soft to deflated and rigid. The infill material on its inside creates the ability for the sphere, together with its neighbouring spheres, to structurally reinforce parts of the population as needed, while also exploring its expansion and ability to introduce deformation. The use of this material-change in the mid-level organization of the population allows the structure to address structural principles available within itself at a much higher level yet remain clear to the relationship of each to each. With these newly established properties, a population of collaborating grippers and spheres can possess and self-regulate themselves as a whole. Setting up clear and context-less beginning conditions allows the research to focus on the basic deformation and stable areas that could emerge from within the population based on various deployments of softness, rigidity, expansion and contraction.

175

[Structuring]

HYDROGEL TESTS

200ml/50pcs

200ml/200pcs

150ml/400pcs

very soft hydrogels at 80% capacity plasticity+ elasticity++++++

soft hydrogels at 80% capacity plasticity+++ elasticity+++

rigid hydrogels at 40% capacity plasticity+++++ elasticity++

fully elastic

elastic/malleable

deformable/gel-like

100ml[W]/100ml[CS]

100ml[W]/50ml[CS]

100ml[W]/20ml[CS]

semi-rigid plasticity+++++ elasticity+

soft plasticity+++ elasticity+++

very liquid plasticity N/A elasticity++++++

deformable/plastic

deformable/elastic

fully elastic/liquid

NON-NEWTONIAN FLUID TESTS

MATERIAL MUTABILITY In our inital tests with hydrogels and non-newtonian fluids, what we found particularly exciting was that these materials had mutable properties which could be finetuned by using watercontet as a control mechanism.

176

[Structuring]

ENVELOPE latex membrane

INFILL loose material

JAMMING AS ACTUATABLE MATERIALITY We wanted to inherit this possibility of changing material properties, so we turned to jamming as a strategy. Whether something would be rigid or soft therefore became a problem of actuation. [ see Two Species : Sphere]

177

[Structuring]

BODY STRUCTURING Balloons filled with small Styrofoam balls make a pseudo-body that can be controlled by breath.

178

[Structuring]

NEUTRAL soft/passive neighborhood of spheres

INFLATED deformation introduced

JAMMED rigid sphere neighborhood

POPULATION ACTUATION The balloons expand and contract to represent the effect of one sphere on another within a body, with the goal effect being movement and or structural performance.

179

[Structuring]

MECHANICAL CONTROL When grippers and spheres have formed a body the spheres inflate to fill in the gaps between the grippers and jam to structure the body. This structuring method remains the same in high populations.

180

[Structuring]

181

[Structuring]

PHYSICAL BODY FORMING A physical body is forming by corralling spheres. In the background an already formed body is beginning upward movement.

182

[Structuring]

BODY POP-UP Bodies prepare to unify the gripper net for esophagus movement. (see page 240)

183

[Structuring]

ACTUATED BODY This is also a model that explores the effects of alternating actuation towards creating movement.

184

[Structuring]

ACTUATED BODY This is also a model that explores the element of structuring. Its corners inflate and deflate to create a bending motion.

185

[Structuring]

BODY MOBILITY By choreographing the inflation of the spheres in a body in different ways mobility is achieved.

186

[Structuring]

BODY MOBILITY When the spheres are pressurized in a choreographed way in a linear body, the body acts as a worm and slowly scoots along.

187

[Structuring]

HIGH POPULATION BODY Spheres and grippers converge building up an actuatable body.

188

[Structuring]

189

[Structuring]

BODY FORMATION Mid-population sized body in formation.

190

[Structuring]

START STATE dettached

ACTUATION spheres start to actuate

BODIES FORM grippers bind spheres

INFLATE deformation + softness

JAM rigidity + stability

BODY ACTUATION Testing behaviors of a formed body once it starts actuating.

191

[Structuring]

GESTURING IN MID-SIZE POPULATION Choreography of inflation in mid-size population.

192

[Structuring]

GESTURING IN MID-SIZE POPULATION Attempts at creating gestures that can be translated into mobility of the collaborative model.

193

[Structuring]

STRUCTURING MODEL A linear body can bend and twist to form an curve.

194

[Structuring]

SINGLE MEMBER Here grippers are shown and sphere are implied through inflation/deflation, which is the mechanism that allows the body to bend in various ways.

195

[Structuring]

MULTIPLE MEMBERS Anonymous setups are used to predict and abstract behaviors of a mid-size population once material properties of the population are changed locally.

196

[Structuring]

OBSERVING BEHAVIOURS / ACHIEVING A BASIC GOAL The most direct goal these populations have is achieving the highest possible average height.

197

[Structuring]

pressurizable partition

pink = INFLATED[soft] blue = JAMMED[rigid]

RADIAL MEMBERS Testing maximum height rulesets on radial members that emerge in mid-population.

198

[Structuring]

RADIAL MEMBERS Testing maximum height rulesets on radial members that emerge in mid-population.

199

[Population Communication]

HIGH POPULATION Once the specie count greatly increases it becomes necessary to create simple rules of local interaction in order to address the problem of self-regulatory functioning.

200

[Population Communication]

POPULATION COMMUNICATION MASS COMMUNICATION INSIDE A HIGH POPULATION Leading into the part of the research concerned with high population management within these collaborating taxonomies, the main problem of control became subsumed into the question of self-regulatory ability of the interacting populations. This is where inter-species communication simultaneously occurs on different levels of organization and carries over these multiple scales which determine global outcomes in the system. Therefore we start small - by defining an element with a low â&#x20AC;&#x153;limit of visionâ&#x20AC;? able to gather only very locally based information. The system is posited in a way where the rules of interaction are based on very localized exchange on the scale of one-to-one. Because interactions occur and are resolved on a highly localized level, they are effectively disabled from directly accessing and knowing what kind of global conditions they generate and inhabit. However this does not necessarily diminish the generative qualities and reproducibility of behavioural patterns of the system as a whole. Therefore, the communication patterns of the elements are abstracted into them gaining access to their immediate neighbourhoods and becoming aware of the numbers of other elements currently within their range. These local neighbourhood metrics then become resolved in two ways, with the element either becoming a caller element (sending out signals to other to come closer) or a listening element (waiting for external input from caller elements). What these rules of local interactions are and how they become resolved specifically, will be explained in the coming chapter.

201

[Population Communication]

“...a system of living cells builds a pattern and succeeds in doing so with no external directing influence, such as a template in the environment or directions from a leader...”

SELF-ORGANIZING PROPERTIES OF LIVING SYSTEMS Camazine, S. (2001). Self-organization in biological systems. Princeton, N.J.: Princeton University Press, p.8.

202

[Population Communication]

LIMIT OF VISION [LOCAL AWARENESS]

GLOBAL WORLD VIEW [GLOBAL CONDITIONS]

LOCAL COMMUNICATION The high population communication scenarios are an attempt to use locally distributed information in order to tease out global behaviors.

203

[Population Communication]

RULESETS if N<7 L->C if Na>1 C->L if N==0 L->C CALLER attractor

LISTENER responder

SINGLE ELEMENT counting its neighbors

NEIGHBOR ELEMENT counterparts within range

SERVER mass information sharing

CLUSTER total accessible database

AVAILABLE INFORMATION/ ENCOUNTERED COMPUTATIONAL STRUCTURES Information is acessible to every element in the system. This drives decision making and formation of types of structures or modes the elements can enter or achieve in the population.

204

[Population Communication]

CALLER/LISTENER Caller elements act as attractors that pull the listener elements towards them, while listener elements are passive elements that respond to the callers’ pull. Whether an element achieves either of these states is goverened by conditions referred to as rulesets. Used for creating culling rulesets that limit the emergence of caller elements (eg. if more than one of your neighbors is a caller and you yourself are a caller one of you must become a listener). stimulating redistribution of elements that leads to development of legible morphological characteristics NEIGHBORHOOD Neighborhood is a imited scanning area of each elements, also referred to as the element’s “limit of vision”. Every elements can scan and assess other elements which are within this area. Used for creating the conditions (rulesets) that turn elements into listeners or callers CLUSTER A cluster is a group of elements that identify as one and share information amongst themselves freely through the “main” element referred to as the SERVER. Clusters are temporary affiliations of elements that change over time as new elements join and old elements leave. Used for creating groups of elements referred that perform as one and to switch to mid-size controlling mechanisms rather than only control the system through element-to-element interactions SEEDING POINTS Seeding points are marked by ID number that differentiates between separately deployed populations, keeping their unique IDs the same, thus identifying which original deployment group they belong to, regardless of the interactions that take place over time Used for closely monitoring the migration of elements one separate populations clash.

205

[Population Communication]

STRINGING

206

[Population Communication]

BASIC BEHAVIORS

Stringing This communicational pattern produces a system in which units move through thin pathways radiating from the core of the population through the activation of peripheral units. Basically, the rules create conditions in which every particle that has less than 7 immediate neighbors becomes an attractor. The first phase of development can be described as a process by which all the particles start joining together in a solid aggregation with a high density. Slowly, only the particles on the absolute periphery are able to pass from their inactive into active state, and these peripheral units start forming the beginnings of a string. As time progresses, through simple collision these starting points will push out and start stringing along other particles from the original solid aggregation, creating a thin pathway.

Pulsing In pulsing communicational pattern produces a densely packed aggregation of units. It displays a stable internal metabolism of contraction once a certain number of units inside a local neighborhood are reached. It is achieved through activation of internal particles while an attractive membrane of surface actives promotes fusion of separately emerging pulsers. The ruleset for pulsing is two-fold. First part of the ruleset addresses the peripheral neighborhoods stating that particles with less than 5 neighbors become attractors. Second part of the ruleset addresses the high density neighborhoods of particles (between 14 and 25 neighbors) that exist in the centroid of the pulsar. Most of these particles are logically located in central areas of aggregations because that is the only way that one could expect them to have high neighborhoods at all. The ruleset states that these particles would become attractors, which introduces the internal flex or pulse, which is the inspiration for the name of this behavior.

207

[Population Communication]

popNo. 2000 deplymentPattern Random seedPoints 1

PULSING We first extracted regular behavior based on the specific condition (see top of next page).

208

[Population Communication] #5

# 10

# 11

CONDITIONS X

MEMBRANE creates a membrane of callers on the surface of the population

INTERNAL PULSE generating callers in the centroid# of 15 the population # 16where the average neighborhood is high to create an internal flex X

# 17

# 18

# 19

OUTER NEIGHBOURHOOD: 7# 6# 5# If a unit has more than 5 and less than 11 neighbors it becomes an attractor. Because this is a common occurrence at the edge nearly all edge units are X X X attractors.

INNER NEIGHBOURHOOD: If a unit has more than 20 or less than 25 neighbours it turns into an attractor.

71 #

61 #

51 #

PULSING A breakdown of the bodyplan that is connected to the pulsing ruleset.

209

[Population Communication]

popNo. 2000 deplymentPattern Random seedPoints 1

STRINGING We first extracted regular behavior based on the specific condition (see top of next page).

210

[Population Communication] CONDITIONS

PERIPHERY Creates a STRING seed points on edges CONSITENCY Creates a STRING seed points on edges

THICKNESS Creates a STRING seed points on edges

NO BREAKING: lonely elements automatically turn into callers in order to ensure that the strings do not dettach from the rest of the population

61 #

GREEDIER RULESET: by expanding the ruleset and including neighborhoods of more elements to become callers, it is effectively possible to predict the thickness of the emerging string

EDGE ELEMENTS: only the outter most elements fulfill 51 # the criteria of low neighborhoods, which is why string start to emerge on the edge areas and radiate away from there X

the greedier the ruleset (allowing more attractors) the thicker the string

STRINGING A breakdown of the bodyplan that is connected to the stringing ruleset.

211

[Population Communication]

METABOLISM01 n<05

METABOLISM02 n<05+TIME*150

METABOLISM03 n<20

METABOLISM04 n<10

METABOLISM05 n<35

METABOLISM06 n<05+TIME*20

METABOLISM07 n<05+TIME*100

CONDITIONS/RULESETS AS METABOLISM DRIVERS Further experimentation with the rulesets allowed for more control and by extension more customizible behaviors in high population.

212

[Population Communication]

BODY PLAN EVOLUTION Rulesets produce specific metabolisms that give rise to differently performing creatures.

213

[Population Communication]

ONE = ELEMENTS Fully local awareness

214

[Population Communication]

ONE = GROUP OF ELEMENTS Local and mid-size awareness

215

[Population Communication]

CLUSTERING DIAGRAM Cluster distribution inside a stringing population.

216

[Population Communication]

INITIAL SETUP (Simple packing) +

+ +

STRINGING ACTIVATED (Peripheral units become active) +

+ +

+ + +

+ +

STRING THINNING (Elongation phase) + +

+ +

+ + +

+ +

+ ++

+ +

+ + +

+ +

+ + + +

+ +

BEACONS INITIATED (Units nearest to the centroid of the super-body become activated) +

+ +

+ ++

+ +

++ +

+ ++

+ + +

+ +

+ + +

+ +

+ + + +

+ +

+ + +

+ + + +

+ +

+ + +

+ +

+ + + +

+ + + + + +

SUPER-BODY FORMING (Units change their ID to the ID of the closest beacon) +

+ +

+ + + +

+ +

SECOND PHASE OF STRINGING (String begin to radiate from newly formed cores)

CLUSTER IMPLEMENTED INTO RULESET RESOLUTION The server of ther cluster is contionuously being turned into a caller and thus amasses more elements around itself creating a core-like structure.

217

[Population Communication]

MORPHOLOGICAL TYPING Using clusters to approximate the shape and size of a particular part of a population.

218

[Population Communication]

219

[Population Communication]

initial population deployment

stringing ruleset initiated

MID-POPULATION CONTROLLING MECHANISMS Clusters are used to partially affect the population partially.

220

[Population Communication]

clusters stimulate creation on new core like structures at the end of each string

stringing ruleset reinitiated to begin new growth of trings from the newly formed cores

further evolution of the population

MID-POPULATION CONTROLLING MECHANISMS Sequence population redistribution by using end string clusters as new seeding points.

221

[Population Communication]

SINGLE POINT OF DEPLOYMENT One seeding point.

222

[Population Communication]

MULTIPLE POINTS OF DEPLOYMENT Many seeding points.

223

[Population Communication]

rule01(n<10)

rule02(n<05) rule03(n<15)

rule04(n<25) rule05(n<20)

popNo. 1000(x5) 300(x5) rulesetPattern Uniform/nonUniform nonUniform seedPoints 5

NON-UNIFORM RULESET DEPLOYMENT Non-uniform rulset patterns deployed on separate populations spawn different interacting creatures.

224

[Population Communication]

rule01(n<10)

rule01(n<10) rule01(n<10)

popNo. 1000(x5) Uniform rulesetPattern Uniform/nonUniform seedPoints 5

UNIFORM RULESET DEPLOYMENT Uniform rulset patterns deployed on separate populations spawn similar creatures that easily fuse together.

225

[Population Communication]

popNo. 200(x16) populationPattern nonUniform seedPoints 16

BIASED DENSITY DEPLOYMENT The inital deployment of the population shows different concentration of elements.

226

[Population Communication]

popNo. 200(x16) rulesetPattern Uniform seedPoints 16

UNIFORM DENSITY DEPLOYMENT The initial deployment of the population shows even concentration and distribution of all members.

227

[Growth Strategy]

ESOPHAGEAL MOVEMENT Grippers constrict around the spheres and slowly push them up.

228

[Growth Strategy]

GROWTH STRATEGY However, because all interaction was still constrained to a plane, the challenge was to ascertain what kind of interaction could be expected in the z-axis movement and what kind of rulesets would govern that part of the systemâ&#x20AC;&#x2122;s behaviour. As a response to this we evaluated the interacting qualities of spheres and grippers we constructed a scenario of upwards movement using the clustering level of organization which would locally create beginnings of vertical seeding points in the population, where grippers start constricting around spheres using their pneumaticability to push them up, while the spheres could use their jamming ability to affect the overall rigidity of these emerging stalks. Therefore the terminal height, sphere transfer power and growing bias are all dependent on a scale which is defined as sensitivity to population metrics and interactions if not the sensitivity to actual proportions of the interacting communities. These growth patterns are significant in a sense where they affect prospective next-tier seeding points. Basic goals of each growing stalk is to therefore generate favourable conditions for next tier seeding which means consolidating its position and proximity to other peaks so that they can be bridged together by gripper taxonomies and therefore create new levels for the deployment of the sphere taxonomy and stimulate further growth. With these rulesets in place we began testing on our 2D setups in order to see what kind of configurations we could achieve and speculate into the build-up scenarios which would support these configurations. The resulting setups exploited the intelligence of both the 2D studies and the z-axis movements to start to achieve proto-spatial qualities with tuneable difference, biasing the mass to grow in certain areas in various configurations.

229

[Growth Strategy]

GROWTH STRATEGY EXPERIMENT Time lapse of the effect of magnetic putty interacting with a magnet.

230

[Growth Strategy]

Behavioral and social biology of animals is studied not only in respect to the individuals that comprise groups, but also the relationship of group behavior and how it affects and changes the individual. p. 62

231

[Growth Strategy]

FORMING OF A STALK Mid-level organization of the population.

232

[Growth Strategy]

GRIPPERS AND SPHERES COLLABORATING TO CREATE A STALK Mid-level organization of the population.

233

[Growth Strategy]

LOW POPULATION FORMATION Grippers hold the spheres and form a net to form a low population structure.

234

[Growth Strategy]

ESOPHAGUS MOVEMENT Grippers constrict around spheres and use a pneumatic motion to push them upwards, while the sphere use their jamming ability to affect the overall fidgety of these emerging stalks.

235

[Growth Strategy]

Seeding Point

Z-Movement

Multi Stalk

ReSeeding Point

inital deployment of the population

gripper population constricts around the sphere population, flexing it like a muscle and propelling the spheres upwards

newly formed stalks continue communication in terms of information exchange priroritizing z-axis movement

respawning new deployment areas on a higher level based on the stalks that emerge from underneath

stalk generation

popNo. 200(x25) growthRuleset Unifrom/Biased seedPoints 25

GROWTH STRATEGY Forming of stalks made from gripper nets constricting around sphere populations and pushing the spheres upwards achieving z-axis movement.

236

[Growth Strategy]

reSeeding Area smaller--

reSeeding Area bigger++

Proximity

Minimum Neighboring Stalks

Z-Movement Bias

possibility of bridging neighboring stalks to create new platforms for reseeding

counting neighboring stalks to find at least two others to connect to in order to create stability

biasing growth towards lonelier stalks that are further apart to maximize next level surface for respawning

GROWTH STRATEGY Emergence of higher tiers as reseeding points once the favorable conditions for inter stalk bridging is met.

237

[Growth Strategy]

HIGH POPULATION COMPOSITE Collaborating taxonomies in high population executing z-movement through emerging stalks.

238

[Growth Strategy]

SCENARIOS OF GROWTH Prototypical situations where 2D formations implement growth strategies.

239

[Growth Strategy]

AN ECOLOGY OF GRIPPERS AND SPHERES IN HIGH POPULATION Grippers and spheres are joined together in a high population. This is a freeze frame of the ever-changing ecology.

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[Growth Strategy]

2 meters square

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[Growth Strategy]

STALK GROWTH A new stalk forms near a high population ecology.

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[Growth Strategy]

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[Final Thought for a New Start]

FINAL THOUGHT FOR A NEW START If the idea of working with predesigned blueprints is no longer the goal, the way of thinking about design problems will therefore have to become systemic. System design assumes that the driver of change is the interaction that enables elements to enter different relationships which are continuously made and broken and where the flow and exchange of basic information teases out behaviours that become indicative of higher form of ordering in a high population. Soft, modular robotics becomes a window into this world of speculation about what space and space-making would entail once the building block becomes animate, interacting, selfregulatory responding to the change within itself and others of its kind not by assuming a fixed place inside an assembly but continually computing and interpreting many levels of organization within the system, and aligning its own metabolism with the newly established conditions.

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[Sources]

It was a grey, cool autumn day and all the bees were home, now agitated by the surgery. I finally plunged my hand into the mess of comb. Hot! Ninety-five degrees at least. Overcrowded with 100,000 cold-blooded bees, the hive had become a warmblooded organism. -Kevin Kelly (1994) p. 41

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