A Supplement to Design World - April 2021 www.therobotreport.com
Inside the development
of Sarcos’ Guardian XO exoskeleton page 78
INSIDE: • Designing sit-to-stand motions for lower-limbs exoskeletons ...............................70 • How computer vision, deep learning help exoskeletons adapt movements ...........74
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Designing sit-to-stand motions for lower-limb exoskeletons
Lower-limb exoskeletons are assisting patients with mobility impairments. Up to this point, most can’t support sit-to-stand motions without outside assistance. Steve Crowe | Editorial Director, The Robot Report
Lower-limb exoskeletons are assisting patients with mobility impairments, such as the elderly or people with paraplegia. There are an estimated 185 million people worldwide who use a wheelchair. For many of them, exoskeletons may be a useful addition. Mobility restoration is achieved by the exoskeleton acting in parallel with the user’s limbs and augmenting their joint torques. This external assistance is allowing patients to carry out day-to-day activities that would be otherwise difficult to autonomously achieve in a wheelchair. Most exoskeletons, however, are not able to support sit-to-stand motions without outside assistance. But researchers at the University of Michigan are hoping to change that with a new approach to virtually create and test sit-to-stand and sit-to-crouch-to-stand exoskeleton motions. “We now have a way to systematically design control objectives for highly constrained systems such that the objectives are not in conflict with the contact constraints,” said Eva Mungai, a PhD candidate in Mechanical Engineering. The researcher’s wrote a paper titled “Feedback Control Design for Robust Comfortable Sit-to-Stand Motions of 3D Lower-Limb Exoskeletons.” Similar research on the sit-to-stand activity is o en done with a simplified model due to the complexity that three dimensions 70
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Here are the Kinematics of the Wandercraft Atlante exoskeleton. | University of Michigan
introduces. That work focuses on the sagittal plane, the X-axis of the sit-to-stand problem, while Mungai’s work incorporates sagittal, ontal, and transverse planes, or X, Y, and Z-axes. “While it’s easier to figure out stability for linear systems, it’s quite difficult to analyze for non-linear systems in three dimensions,” said Mungai, who is advised by Jessy Grizzle, professor of electrical and computer engineering and Director of U-M Robotics Institute. Adding to the complexity of the problem is the need to guarantee both an exoskeleton user’s safety and comfort. To address the complexity, Mungai and Grizzle split the problem into three challenges: • Modeling the exoskeleton in 3D • Creating the sit-to-stand motions • Executing and testing the motions to make sure the system operates in real-time to meet the goal while keeping the user comfortable and safe. THE ROBOT REPORT
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According to the U-M researchers, there are only two hands- ee exoskeletons on the market: REX om REX Bionics and Wandercra ’s Atalante. This project focused on Atalante because a detailed model was shared with the researchers. Moreover, because Atalante has been explicitly designed for dynamic walking, it is interesting to seek dynamic standing trajectories that can be achieved with minimal user assistance, and no other assistance, or even no user assistance at all. Wandercra provided the universal robot description file for Mungai to use for modeling and generation of chair-to-stand and chair-to-crouch-to-stand motions, which could then undergo testing. Each leg of the Atalante exoskeleton has six actuated joints: ontal hip joint, transverse hip joint, sagittal hip joint, sagittal knee joint, sagittal ankle joint and henke ankle joint. Encoders are located on each actuated joint and an inertial measurement unit is located at the torso. The adjustable thigh and shank links on Atalante allow www.therobotreport.com
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The Robot Report Motor torque limits used for optimization Name
Maximum Torque (N)
Nominal Torque (N)
Henke Ankle Joint
90
82
Sagittal Ankle Joint
192
184
Sagittal Knee Joint
219
124
Sagittal Hip Joint
219
124
Transverse Hip Joint
180
124
Frontal Hip Joint
350
198
it to be worn by a variety of users. There are four force sensors on the corner of each foot that allow for the detection of ground reaction forces (GRF). The exoskeleton is attached to the user via multiple straps on each leg and foot, and a belt/jacket set on the torso. Atalante has been certified for use in the European Union and is operational in various rehabilitation centers in France. A static sit-to-stand motion requires intermediate poses to be stable throughout the motion, while dynamic motion refers to a continuous trajectory, which, like a dynamic walking gait, does not guarantee stability at intermediate points of time. Even though the “inherent stability” of a static motion appears to be more desirable than a dynamic motion, the severe constraints required by the trajectory are often incompatible with hardware limitations (e.g., joint torque limits). External force from the user, either by pushing downward on the arms of a chair, crutches, or functional electrical stimulation (FES), have been used to achieve
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assisted sit-to-stand motions. Allowing for the user to apply an external force can enhance stability of the motion as well as user confidence in the motion. Constrained optimization, performed using the Fast Robot Optimization and Simulation Toolkit (FROST), was used to ensure the open-loop behavior of the two motions were feasible. The researchers derived the dynamic equations using the full dynamic model of the exoskeleton, and incorporated the user force in the equations of motion. The equations of motion for both the sit-to-stand and sit-to-crouch-to-stand motions were highly constrained, due to the various contact points, and therefore underdetermined with respect to the motor torques. To address this, the team developed, for a computed-torque controller, a novel way of systematically designing virtual constraints so they ‘‘do not fight’’ the contact constraints for highly constrained systems. To analyze and compare the closed-loop behavior of the two motions, we designed two QP-based computed-torque controllers and conducted physically motivated robustness tests. The choice of a QP-based controller allowed to select the vector of motor torques of smallest norm that satisfied the control objectives, as expressed by a set of virtual constraints. The results indicated both motions can equally handle variations to user characteristics and user force disparities. In fact, the analysis showed it is possible to successfully stand up with no user force under both motions. The sit-to-crouch-to-stand motion, however, was more well equipped to handle asymmetric perturbations, while the chair-to-stand excelled at handling variations to the chair height. To improve the operational range of either motion, for perturbations that result in incorrect contact forces, a chair with a high iction coefficient could be specified or the motion could be redesigned for the new environmental conditions. To check the effectiveness of our method, the researchers compared their control objectives and sit-to-stand controller to those found in the literature. They said their control objectives were better at respecting contact constraints and resulted in motions that required less torso pitch acceleration. Even though the methods presented are for the Atalante exoskeleton, the researchers claimed their methodology can be adopted for other motions with multiple contact points and other exoskeletons or humanoids. The next steps for this work would be implementation on hardware. Also an important step in this work is the focus on comfort. “It’s really hard to quanti user comfort, but it’s so important, and this is just a beginning,” said Mungai. RR
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How
computer vision, deep learning help exoskeletons adapt movements
Similar to autonomous cars that drive themselves, autonomous exoskeletons walk themselves and adapt to their surroundings. Steve Crowe | Editorial Director, The Robot Report
Researchers are developing exoskeletons capable of making control decisions on their own using computer vision and deep learning. This enables an exoskeleton to mimic how able-bodied people walk by seeing their surroundings and adjusting their movements. “We’re giving robotic exoskeletons vision so they can control themselves,” said Brokoslaw Laschowski, a PhD candidate in systems design engineering who leads a University of Waterloo research project called ExoNet. Exoskeleton legs operated by motors already exist, but users must manually control them via smartphone applications or joysticks. “That can be inconvenient and cognitively demanding,” said Laschowski. “Every time you want to perform a new locomotor activity, you have to stop, take out your smartphone and select the desired mode.” To address that limitation, the researchers fitted exoskeleton users with wearable cameras and are optimizing computer so ware to process the video feed to accurately recognize stairs, doors and other features of the surrounding environment. Supplementing neuromuscular-mechanical data with information about the upcoming walking environment could improve the highlevel control performance, according to the researchers. Similar to the
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The researchers are also working to improve the energy efficiency of motors for exoskeletons and prostheses by using human motion to selfcharge the batteries. | University of Waterloo
human visual system, environment sensing would precede modulation of the patient’s muscle activations and/or walking biomechanics, enabling more accurate and realtime locomotion mode transitions. Environment sensing could also be used to adapt low-level reference trajectories (changing toe clearance corresponding to an obstacle height) and optimal path planning (identifying opportunities for energy regeneration). Preliminary research has shown that supplementing an automated locomotion mode recognition system with environment information can improve the classification accuracies and decision times compared to excluding terrain information. Building the ExoNet dataset The researchers used an NVIDIA TITAN GPU for neural network training and real-time image classification of walking environments. They collected over 5.6 million images of human locomotion environments to create a database dubbed ExoNet — which was used to train the initial model, THE ROBOT REPORT
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developed using the TensorFlow deep learning framework. The researchers claim ExoNet is the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. The researchers said the lack of an open-source, large-scale dataset of human locomotion environment images has impeded the development of environment-aware control systems for lower-limb exoskeletons. To fix this, the researchers outfitted one subject with a lightweight wearable smartphone camera system. The smartphone contained two 12-megapixel RGB rear-facing cameras and one 7-megapixel front-facing camera. And with 512-GB of memory storage, and a 64-bit ARM-based integrated circuit with six-core CPU and four-core GPU, the system supported onboard machine learning for real-time environment classification. The subject walked around unknown outdoor and indoor environments while collecting images with occlusions, signal noise, and intraclass variations. Data was collected at various times throughout the day to incorporate different lighting www.therobotreport.com
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The Robot Report Reference Da Silva et al. (2020)
Sensor
Position
Dataset Images
Resolution
Classes
RGB camera
Lower-limb
3,992
512 x 512
6
Diaz et al. (2018)
RGB camera
Lower-limb
3,992
1,080 x 1,920
6
Khademi and Simon (2019)
RGB camera
Waist
7,284
224 x 224
3
Krausz and Hargrove (2015)
RGB camera
Head
5
928 x 620
2
Krausz et al. (2015)
Depth camera
Chest
170
80 x 60
2
Krausz et al. (2019)
Depth camera
Waist
4,000
171 x 224
5
RGB camera
Chest
34,254
224 x 224
3
Laschowski et al. (2019) Massalin et al. (2018)
Depth camera
Lower-limb
402,403
320 x 240
5
Novo-Torres et al. (2019)
RGB camera
Head
40,743
128 x 128
2
Varol and Massalin (2016)
Depth camera
Lower-limb
22,932
320 x 240
5
Zhang et al. (2019)
Depth camera
Lower-limb
7,500
224 x 171
5
Zhang et al. (2019)
Depth camera
Waist
4,016
2,048 Point Cloud
3
Zhang et al. (2020)
Depth camera
Lower-limb
7,500
100 x 100
5
Zhang et al. (2020)
RGB camera
327,000
1,240 x 1,080
6
ExoNet
RGB camera
922,790
1,280 x 720
12
Head and lower-limb
conditions. The same environment was never sampled twice to maximize diversity of the dataset. Data were collected throughout the summer, fall, and winter seasons to incorporate different weathered surfaces like snow, grass, and multicolored leaves. Approximately 923,000 images in ExoNet were manually labeled and organized into 12 classes. Images were labeled according to exoskeleton and control functionality, rather than a purely computer vision perspective. For instance, images of level-ground environments showing either pavement or grass were not differentiated since both surfaces would use the same levelground walking state controller. In contrast, computer vision researchers might label these different surface textures as separate classes. A potential limitation of the ExoNet database is the 2D nature of the environment information. Whereas RGB cameras measure light intensity information, depth cameras also provide distance measurements. Depth cameras work by emitting infrared light and calculate distances by measuring the light time-of-flight between the camera and physical environment. Depth measurement
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Chest
accuracies typically degrade in outdoor lighting conditions (e.g., sunlight) and with increasing measurement distance. Consequently, most environment recognition systems using depth cameras have been tested in indoor environments and have had limited capture volumes. Assuming mobile computing, the application of depth cameras for environment sensing would also require lower-limb exoskeletons to have embedded microcontrollers with significant computing power and minimal power consumption, the specifications of which are not supported by existing untethered systems. These practical limitations motivated the decision to use RGB images. The camera images could be fused with the smartphone IMU measurements to improve high-level control performance. For example, if an exoskeleton or prosthesis user unexpectedly stops while walking toward an incline staircase, the acceleration measurements would indicate static standing rather than stair ascent, despite the staircase being accurately detected in the field-of-view. www.therobotreport.com
Comparison of the ExoNet database with previous environment recognition systems for lower-limb exoskeletons. | University of Waterloo
Sending instructions to motors The next phase of the ExoNet research project will involve sending instructions to motors so that robotic exoskeletons can climb stairs, avoid obstacles or take other appropriate actions based on analysis of the user’s current movement and the upcoming terrain. “Our control approach wouldn’t necessarily require human thought,” said Laschowski, who is supervised by engineering professor John McPhee, the Canada Research Chair in Biomechatronic System Dynamics. “Similar to autonomous cars that drive themselves, we’re designing autonomous exoskeletons and prosthetic legs that walk for themselves.” The researchers are also working to improve the energy efficiency of motors for robotic exoskeletons and prostheses by using human motion to self-charge the batteries. The research team also includes engineering professor Alexander Wong, the Canada Research Chair in Artificial Intelligence and Medical Imaging, and William McNally, also a PhD candidate in systems design engineering and a student member of Waterloo.ai. RR THE ROBOT REPORT
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Inside
the development of Sarcos’ Guardian XO exoskeleton Ben Wolff, chairman and CEO of Sarcos Robotics, discusses the evolution and challenges of developing its full-body exoskeleton. Steve Crowe | Editorial Director, The Robot Report
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Based in Salt Lake City, Sarcos Robotics began in the 1980s as a spinout from the University of Utah, with a legacy of innovation found in applications that range from advanced humanoid robots and dinosaurs at theme parks, to NASA spacesuit-testing equipment, prosthetic limbs, and MEMS sensors. It has also been developing exoskeletons for more than 20 years. The Defense Advanced Research Projects Agency (DARPA) originally funded the development of the Guardian XO fully-body, powered exoskeleton in 2000 as it was looking to enable soldiers to carry more weight on their backs. Flash forward to 2021, and many iterations and improvements later, the Guardian XO is starting to make its way into more commercial industries, including aviation and aerospace, construction and logistics. Sarcos began testing with select customers and partners in the first few months of 2020, including the company’s Exoskeleton Technical Advisory Group (X-TAG) and the U.S. military, before COVID-19 shut down the majority of job sites. Testing of the Guardian XO will resume in 2021 once it is safe for Sarcos’ customers and partners. The company expects the commercial product to begin shipping to customers in 2022. Sarcos raised $40 million in Series C funding in September 2020 that will be used for commercial production of the Guardian XO. It also announced in early April that it will become publicly listed through a merger with Rotor Acquisition Corp., a publicly-traded special purpose acquisition company (SPAC). The combined company, which has a valuation of $1.3 billion, is expected to trade on Nasdaq under the ticker symbol STRC. We recently sat down with Sarcos’ chairman and CEO Ben Wolff, who discussed the evolution of Guardian XO, the main challenge of designing the system, why Robotics-
The Guardian XO exoskeleton enables operators to safely lift and manipulate up to 200 lb without fatigue or strain. | Sarcos Robotics
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The Robot Report We’re not only about vertical lifting, we’re about being able to dexterously manipulate heavy and challenging objects and improving the productivity of many people because of what you can let them manipulate.
as-a-Service (RaaS) is the proper selling method for Sarcos and more. This interview was adapted from Wolff’s recent appearance on The Robot Report Podcast. To listen to the full conversation, check out The Robot Report Podcast wherever you listen to your podcasts.
The Guardian XO exoskeleton offers 24 degrees of freedom to help operators move freely. | Credit: Sarcos Robotics
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Why is Sarcos building the Guardian XO full body, powered exoskeleton? Our focus from the start has been about how to enhance what humans can do with their upper body. Folks might not know, but we started back in the 1980s, working on the first electrically-actuated prosthetic arm. That gave our team a deep foundation in biomechanics and the intimate pairing between humans and machines. We evolved from there into focusing on humanoid robots. We developed the exoskeleton as really being a full-body, powered humanoid robot, with the added complexity of trying to create room inside of the robot for a human to intuitively control the robot. We took the challenge of a humanoid robot form factor and raised it by a factor of 10. And that’s where we are. The thesis is we’re giving people superhuman strength, safely. We’re going to allow people in challenging work environments to lift up to 200 lb and feel like they’re only lifting five or 10, putting no stress or strain on the human body. And it’s not just about lifting. There are a lot of machines out there that can lift - whether it’s a forklift or lift truck.
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What’s the most interesting object that has been lifted with the Guardian XO? I’ll give you an example from the defense logistics side. You can find images all over the internet of Navy personnel lifting 150-lb missiles to mount them on the underside of a plane. It’s a great example because you see six big, strong people standing shoulder to shoulder trying to lift this material and you see the strain on their face. We have demonstrated the ability to lift that specific form factor at that weight with one person. We demonstrated at [CES 2020] being able to do things like use 60-lb torque wrenches, effortlessly, for mounting a tire and securing the nuts on the tire for airplane landing gear. We can go into cargo environments and lift large, bulky items of cargo with one person. That’s becoming particularly relevant in this COVID-19 environment. It’s pretty hard to do a two-person lift and maintain six feet of social distancing. How much training is required for users to wear and operate the Guardian XO? To be able to simply get in the suit and start using it to manipulate objects and to walk, it takes under one hour to make the machine start to move in a very intuitive way so that you don’t have to think about managing the machine and you can focus 100% on the task at hand. Now we do have more extensive training than that because it’s not just about knowing how to operate the machine, turn it on and off and get in and out. It’s also about how to be aware of the environment in which you’re operating. Equate it to forklift training, for example. It’s one thing to learn how to drive the forklift and to lift heavy objects. It’s another thing to understand that you’re driving a machine that can create damage in your environment if you’re not careful. Learning about situational awareness and how to drive at appropriate speeds, and how to manage the power of the forklift is a different set of training issues. THE ROBOT REPORT
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2 Conceptual rendering of the multi-jointed robotic arm of a surgical system.
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The Robot Report That’s where we put more time into training. Ultimately, we expect operators to become certified to use the exoskeleton with about a day and a half or two days of complete training. The Guardian XO is designed to be worn for close to a full 8-hour shi . How difficult was it to get to that point because there’s a lot of biomechanics that goes into making it comfortable and usable for that amount of time? The ability to use it for a full shi has ergonomic issues associated with comfort and usability, but there’s also just the issue of power. We had to tackle both of those issues. Making humanoid robots walk and carry load consumes an awful lot of power. The first version of the exoskeleton we produced years ago consumed about 6800 watts of power on average per hour. To give you context, something like a DJI drone is using somewhere around 3000-4000 watts of power, which is why it can stay alo for 20 or 30 minutes. Today, we are able to operate the robot walking three miles an hour, carrying 160-lb load at less than 500 watts. That
means we can start using today’s lithium ion, off-the-shelf batteries to have extended work life and perform in all the ways the operator wants it to. In terms of ergonomics, because of the nature of our control system, the machine is very comfortable. Although you’ve got a large machine around you, most of the operators I’ve interacted with said it feels like you’re wearing a backpack that might weigh five or 10 lb. But when you li 200 lb, you only feel like you’re li ing five or 10. So we’ve taken all of the stress and strain off of the human body. Are there plans to shrink down the size of the Guardian XO? The size is really dependent on the laws of physics and what you’re trying to li . If you think about the forkli analogy I used earlier, you can’t take a forkli designed to li 30,000 lb and materially shrink the size of it and still li 30,000 lb. We think the biggest market opportunity for us is initially to be able to li up to 200 lb. That’s going to require a structure similar to what we’ve got. The laws of physics kind of mandate that.
Changing the laws of physics seems complicated. Having said that, when you decide there might be a large market opportunity to li 80 lb with a single person instead of 200, absolutely, the machine can be smaller in nature. We’re looking at all of that. And we’ve already gone the other direction with the Guardian GT. It’s a machine that can li 1,000 lb, 500 in each arm, that is tele-operated and based on the same basic design as the exoskeleton. But we haven’t gone the other direction yet to make it smaller. Why is Robotics-as-a-Service (RaaS) the correct business model for Sarcos? We build a machine that is the next generation of a unit of labor. We position ourselves as a next-generation labor contractor providing units of labor that can augment an existing workforce. The value proposition is that for roughly the fully burdened cost of a single human worker, we will deliver the output of anywhere between four and 10 workers, while also eliminating occupational back injuries, which has a tremendous cost.
Guardian XO for airline operations Airline employees engaged in the regular loading and unloading of heavy, bulky, or awkwardly sized luggage and other materials are faced with ongoing physical stressors. According to the National Institute for Occupational Safety and Health, baggage handlers li about five to 10 bags a minute, each of which weighs between 32 and 70 lb (14 and 31 kg), over the course of a standard eight-hour shi . The potential for musculoskeletal injuries is exacerbated by the twisting, pushing, pulling, and kneeling required to stack and shi heavy baggage. In cases of airline disruptions – such as unloading delays, aircra diversions, and flight cancellations – employees must sort baggage manually to prioritize short-connection baggage, set up areas for mishandled bags or return bags to passengers, which o en leads to disruption and confusion for employees and passengers alike. With the International Air Transport Association (IATA) expecting air passengers to double to 8.2 billion in 2037, airlines must enact solutions that support overburdened employees and address passenger pain points in order to navigate continued growth successfully. Delta Airlines in 2020 became the first company whose ont-line employees worked directly with Sarcos to determine potential operational uses for the Guardian XO. Potential uses at Delta could include handling eight at Delta Cargo warehouses, moving maintenance components at Delta TechOps, or li ing heavy machinery and parts for ground support equipment. Delta first started working with Sarcos in 2018 as part of its “X-TAG,” or exoskeleton technical advisory group, representing the aviation sector.
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Delta demo at CES 2020. | Credit: Sarcos Robotics
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The Robot Report If we can provide a machine that is part of payroll costs and provides greater productivity in an environment where it’s hard to find enough skilled workers and eliminates the cost of back injuries for workers, that’s a win for everybody. It also means our customer does not have to write a big check up ont. They get to pay as they go. If the robot isn’t providing the value or utility they expect, they haven’t made a big technology bet, which is important when you’re talking about bringing a brand new class of machine to market the way we are. It’s a win for our customers. Now there are some customers that would rather it be a capital item as opposed to an operating expense, and we can still maintain that basic value proposition of a RaaS model and deliver that kind of accounting treatment for our customer. So it’s not so much about capital expenses (CapEx) or operational expenses (OpEX), it’s more about decreasing technology risk, ensuring that a unique platform will be serviced and maintained and to ensure it continues to show up everyday and do its job. What has been the most difficult technical challenge building the Guardian XO? That’s a much longer conversation. We’ve been at it for 20 years and hundreds of millions of dollars have been invested to get to where we are. But the challenges around power consumption have been huge. If you couldn’t get the power consumption down and be able to deliver extended operating life without having to be tethered, you just didn’t have a viable product that was so intuitive you didn’t have to think about it.
That was the original vision of Robert Heinlein when he described exoskeletons in Starship Troopers back in 1959. The first concept for exoskeletons was that you could use them so intuitively, you didn’t have to think about it. That really has to be the goal. When you’re talking about a machine that has 125 sensors on it, compute power that is equivalent to three Intel servers today and a series of subsystems, it’s got to be intuitive to use, it’s got to be robust, and it’s got to be low power. Those were the big issues that drove us over the last 20 years. On a high level, how were you able to get the control experience right? So much of it has to do with the right integration of the right sensors, coupled with the so ware scheme we’ve developed over the years. There are folks who take different approaches to sense what the human body intends to do om a movement perspective. Elon Musk recently talked about putting chips in brains, you see others using sensors affixed to the skin to try and understand and interpret neurological stimuli and make informed conclusions. And then there’s our approach, which is different than either of those. And I think we’ve got a very novel patented approach to it. It’s really this combination of compute power, the right kind of sensors in the right place in the right number, and the algorithms and so ware that we have that work together as a seamless package to deliver that kind of intuitive control and response. RR
Ben Wolff Ben Wolff serves as the chairman, CEO, president and is the largest shareholder of Sarcos Robotics. In his various roles, he oversees the strategic direction of the company and engages with partners, customers and investors. For more information, visit https://www.sarcos.com.
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FAULHABER MICROMO www.faulhaber.com 14881 Evergreen Ave Clearwater, FL 33762 USA
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FUTEK We make innovation possible FUTEK Advanced Sensor Technology specializes in creating inventive sensor solutions for today’s leading tech innovators: • Load cells • Torque sensors • Pressure sensors • Multi-axis sensors • Instruments • Software Our end-to-end measurement products and services include sensors, amplifiers, and calibration, allowing you to streamline and optimize your system and achieve better results at a lower cost than legacy solutions. All our products are made in the USA. To learn more, visit www.futek.com.
www.therobotreport.com
FUTEK Advanced Sensor Technology, Inc. 10 Thomas Irvine, CA 92618 USA www.futek.com +1 (949) 465-0900
THE ROBOT REPORT
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Connectors 4 Robots LEMO connectors are used on collaborative robots for industrial applications but also for control, articulated manipulator, and automation systems. As robots become more complex, LEMO connectors enable connecting sensors, motors and actuators in an efficient way, even when the cabling layout is very dense. Thanks to the Push-Pull system, the connector can be easily mated and un-mated allowing reduced maintenance and installation time. LEMO connectors are used extensively on quadrupedal and other legged robots, as well as on wheeled robots. LEMO’s high-speed circular connector (CAT6A signals) can be built into 2K/ 2T/ 2B series, offer IP68 watertightness and full EMC. Learn More at https://www.lemo.com/en/application/robotic-connector LEMO USA, Inc. 635 Park Court Rohnert Park, CA 94928 www.lemo.com info-us@lemo.com Tel: 707.206.3700
New England Wire Technologies Advancing innovation for over 100 years Why accept a standard product for your custom application? NEWT is committed to being the premier manufacturer of choice for customers requiring specialty wire, cable and extruded tubing to meet existing and emerging worldwide markets. Our custom products and solutions are not only engineered to the exacting specifications of our customers, but designed to perform under the harsh conditions of today’s advanced manufacturing processes. Cables we specialize in are LITZ, multi-conductor cables, hybrid configurations, coaxial, twin axial, miniature and micro-miniature coaxial cables, ultra flexible, high flex life, low/high temperature cables, braids, and a variety of proprietary cable designs. Contact us today and let us help you dream beyond today’s technology and achieve the impossible.
THE ROBOT REPORT
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NEW ENGLAND WIRE T E C H N O LO G I E S
www.therobotreport.com
Contact info: New England Wire Technologies www.newenglandwire.com 603.838.6624
April 2021
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Flexible gripper tooling puts you in control of your processes Deployment of robots with flexible gripper tooling has never been faster. Build your own custom gripping EOAT components and start loading your CNC machines in minutes! SCHUNK Flex Grip Tools incorporates standard gripping modules: including finger tooling, pneumatic valves, sensors and modular mounting hardware kits – everything you need to get up and running quickly. Flexibility in manufacturing and automation is all about being able to modify an existing solution to work for a new task – with Flex Grip Tools standard components can easily be switched out to adapt the process to a new task with minimal effort or re-design, keeping costs low and downtime short.
Contact Info: SCHUNK 211 Kitty Hawk Drive Morrisville, NC 27560 www.schunk.com Phone: 919-572-2705
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