Tag Archives: environment
#435683 How High Fives Help Us Get in Touch With ...
The human sense of touch is so naturally ingrained in our everyday lives that we often don’t notice its presence. Even so, touch is a crucial sensing ability that helps people to understand the world and connect with others. As the market for robots grows, and as robots become more ingrained into our environments, people will expect robots to participate in a wide variety of social touch interactions. At Oregon State University’s Collaborative Robotics and Intelligent Systems (CoRIS) Institute, I research how to equip everyday robots with better social-physical interaction skills—from playful high-fives to challenging physical therapy routines.
Some commercial robots already possess certain physical interaction skills. For example, the videoconferencing feature of mobile telepresence robots can keep far-away family members connected with one another. These robots can also roam distant spaces and bump into people, chairs, and other remote objects. And my Roomba occasionally tickles my toes before turning to vacuum a different area of the room. As a human being, I naturally interpret this (and other Roomba behaviors) as social, even if they were not intended as such. At the same time, for both of these systems, social perceptions of the robots’ physical interaction behaviors are not well understood, and these social touch-like interactions cannot be controlled in nuanced ways.
Before joining CoRIS early this year, I was a postdoc at the University of Southern California’s Interaction Lab, and prior to that, I completed my doctoral work at the GRASP Laboratory’s Haptics Group at the University of Pennsylvania. My dissertation focused on improving the general understanding of how robot control and planning strategies influence perceptions of social touch interactions. As part of that research, I conducted a study of human-robot hand-to-hand contact, focusing on an interaction somewhere between a high five and a hand-clapping game. I decided to study this particular interaction because people often high five, and they will likely expect robots in everyday spaces to high five as well!
I conducted a study of human-robot hand-to-hand contact, focusing on an interaction somewhere between a high five and a hand-clapping game. I decided to study this particular interaction because people often high five, and they will likely expect robots to high five as well!
The implications of motion and planning on the social touch experience in these interactions is also crucial—think about a disappointingly wimpy (or triumphantly amazing) high five that you’ve experienced in the past. This great or terrible high-fiving experience could be fleeting, but it could also influence who you interact with, who you’re friends with, and even how you perceive the character or personalities of those around you. This type of perception, judgement, and response could extend to personal robots, too!
An investigation like this requires a mixture of more traditional robotics research (e.g., understanding how to move and control a robot arm, developing models of the desired robot motion) along with techniques from design and psychology (e.g., performing interviews with research participants, using best practices from experimental methods in perception). Enabling robots with social touch abilities also comes with many challenges, and even skilled humans can have trouble anticipating what another person is about to do. Think about trying to make satisfying hand contact during a high five—you might know the classic adage “watch the elbow,” but if you’re like me, even this may not always work.
I conducted a research study involving eight different types of human-robot hand contact, with different combinations of the following: interactions with a facially reactive or non-reactive robot, a physically reactive or non-reactive planning strategy, and a lower or higher robot arm stiffness. My robotic system could become facially reactive by changing its facial expression in response to hand contact, or physically reactive by updating its plan of where to move next after sensing hand contact. The stiffness of the robot could be adjusted by changing a variable that controlled how quickly the robot’s motors tried to pull its arm to the desired position. I knew from previous research that fine differences in touch interactions can have a big impact on perceived robot character. For example, if a robot grips an object too tightly or for too long while handing an object to a person, it might be perceived as greedy, possessive, or perhaps even Sméagol-like. A robot that lets go too soon might appear careless or sloppy.
In the example cases of robot grip, it’s clear that understanding people’s perceptions of robot characteristics and personality can help roboticists choose the right robot design based on the proposed operating environment of the robot. I likewise wanted to learn how the facial expressions, physical reactions, and stiffness of a hand-clapping robot would influence human perceptions of robot pleasantness, energeticness, dominance, and safety. Understanding this relationship can help roboticists to equip robots with personalities appropriate for the task at hand. For example, a robot assisting people in a grocery store may need to be designed with a high level of pleasantness and only moderate energy, while a maximally effective robot for comedy roast battles may need high degrees of energy and dominance above all else.
After many a late night at the GRASP Lab clapping hands with a big red robot, I was ready to conduct the study. Twenty participants visited the lab to clap hands with our Baxter Research Robot and help me begin to understand how characteristics of this humanoid robot’s social touch influenced its pleasantness, energeticness, dominance, and apparent safety. Baxter interacted with participants using a custom 3D-printed hand that was inlaid with silicone inserts.
The study showed that a facially reactive robot seemed more pleasant and energetic. A physically reactive robot seemed less pleasant, energetic, and dominant for this particular study design and interaction. I thought contact with a stiffer robot would seem harder (and therefore more dominant and less safe), but counter to my expectations, a stiffer-armed robot seemed safer and less dominant to participants. This may be because the stiffer robot was more precise in following its pre-programmed trajectory, therefore seeming more predictable and less free-spirited.
Safety ratings of the robot were generally high, and several participants commented positively on the robot’s facial expressions. Some participants attributed inventive (and non-existent) intelligences to the robot—I used neither computer vision nor the Baxter robot’s cameras in this study, but more than one participant complimented me on how well the robot tracked their hand position. While interacting with the robot, participants displayed happy facial expressions more than any other analyzed type of expression.
Photo: Naomi Fitter
Participants were asked to clap hands with Baxter and describe how they perceived the robot in terms of its pleasantness, energeticness, dominance, and apparent safety.
Circling back to the idea of how people might interpret even rudimentary and practical robot behaviors as social, these results show that this type of social perception isn’t just true for my lovable (but sometimes dopey) Roomba, but also for collaborative industrial robots, and generally, any robot capable of physical human-robot interaction. In designing the motion of Baxter, the adjustment of a single number in the equation that controls joint stiffness can flip the robot from seeming safe and docile to brash and commanding. These implications are sometimes predictable, but often unexpected.
The results of this particular study give us a partial guide to manipulating the emotional experience of robot users by adjusting aspects of robot control and planning, but future work is needed to fully understand the design space of social touch. Will materials play a major role? How about personalized machine learning? Do results generalize over all robot arms, or even a specialized subset like collaborative industrial robot arms? I’m planning to continue answering these questions, and when I finally solve human-robot social touch, I’ll high five all my robots to celebrate.
Naomi Fitter is an assistant professor in the Collaborative Robotics and Intelligent Systems (CoRIS) Institute at Oregon State University, where her Social Haptics, Assistive Robotics, and Embodiment (SHARE) research group aims to equip robots with the ability to engage and empower people in interactions from playful high-fives to challenging physical therapy routines. She completed her doctoral work in the GRASP Laboratory’s Haptics Group and was a postdoctoral scholar in the University of Southern California’s Interaction Lab from 2017 to 2018. Naomi’s not-so-secret pastime is performing stand-up and improv comedy. Continue reading →
Posted in Human Robots
#435681 Video Friday: This NASA Robot Uses ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Let us know if you have suggestions for next week, and enjoy today’s videos.
Robots can land on the Moon and drive on Mars, but what about the places they can’t reach? Designed by engineers as NASA’s Jet Propulsion Laboratory in Pasadena, California, a four-limbed robot named LEMUR (Limbed Excursion Mechanical Utility Robot) can scale rock walls, gripping with hundreds of tiny fishhooks in each of its 16 fingers and using artificial intelligence to find its way around obstacles. In its last field test in Death Valley, California, in early 2019, LEMUR chose a route up a cliff, scanning the rock for ancient fossils from the sea that once filled the area.
The LEMUR project has since concluded, but it helped lead to a new generation of walking, climbing and crawling robots. In future missions to Mars or icy moons, robots with AI and climbing technology derived from LEMUR could discover similar signs of life. Those robots are being developed now, honing technology that may one day be part of future missions to distant worlds.
[ NASA ]
This video demonstrates the autonomous footstep planning developed by IHMC. Robots in this video are the Atlas humanoid robot (DRC version) and the NASA Valkyrie. The operator specifies a goal location in the world, which is modeled as planar regions using the robot’s perception sensors. The planner then automatically computes the necessary steps to reach the goal using a Weighted A* algorithm. The algorithm does not reject footholds that have a certain amount of support, but instead modifies them after the plan is found to try and increase that support area.
Currently, narrow terrain has a success rate of about 50%, rough terrain is about 90%, whereas flat ground is near 100%. We plan on increasing planner speed and the ability to plan through mazes and to unseen goals by including a body-path planner as the first step. Control, Perception, and Planning algorithms by IHMC Robotics.
[ IHMC ]
I’ve never really been able to get into watching people play poker, but throw an AI from CMU and Facebook into a game of no-limit Texas hold’em with five humans, and I’m there.
[ Facebook ]
In this video, Cassie Blue is navigating autonomously. Right now, her world is very small, the Wavefield at the University of Michigan, where she is told to turn left at intersections. You’re right, that is not a lot of independence, but it’s a first step away from a human and an RC controller!
Using a RealSense RGBD Camera, an IMU, and our version of an InEKF with contact factors, Cassie Blue is building a 3D semantic map in real time that identifies sidewalks, grass, poles, bicycles, and buildings. From the semantic map, occupancy and cost maps are built with the sidewalk identified as walk-able area and everything else considered as an obstacle. A planner then sets a goal to stay approximately 50 cm to the right of the sidewalk’s left edge and plans a path around obstacles and corners using D*. The path is translated into way-points that are achieved via Cassie Blue’s gait controller.
[ University of Michigan ]
Thanks Jesse!
Dave from HEBI Robotics wrote in to share some new actuators that are designed to get all kinds of dirty: “The R-Series takes HEBI’s X-Series to the next level, providing a sealed robotics solution for rugged, industrial applications and laying the groundwork for industrial users to address challenges that are not well met by traditional robotics. To prove it, we shot some video right in the Allegheny River here in Pittsburgh. Not a bad way to spend an afternoon :-)”
The R-Series Actuator is a full-featured robotic component as opposed to a simple servo motor. The output rotates continuously, requires no calibration or homing on boot-up, and contains a thru-bore for easy daisy-chaining of wiring. Modular in nature, R-Series Actuators can be used in everything from wheeled robots to collaborative robotic arms. They are sealed to IP67 and designed with a lightweight form factor for challenging field applications, and they’re packed with sensors that enable simultaneous control of position, velocity, and torque.
[ HEBI Robotics ]
Thanks Dave!
If your robot hands out karate chops on purpose, that’s great. If it hands out karate chops accidentally, maybe you should fix that.
COVR is short for “being safe around collaborative and versatile robots in shared spaces”. Our mission is to significantly reduce the complexity in safety certifying cobots. Increasing safety for collaborative robots enables new innovative applications, thus increasing production and job creation for companies utilizing the technology. Whether you’re an established company seeking to deploy cobots or an innovative startup with a prototype of a cobot related product, COVR will help you analyze, test and validate the safety for that application.
[ COVR ]
Thanks Anna!
EPFL startup Flybotix has developed a novel drone with just two propellers and an advanced stabilization system that allow it to fly for twice as long as conventional models. That fact, together with its small size, makes it perfect for inspecting hard-to-reach parts of industrial facilities such as ducts.
[ Flybotix ]
SpaceBok is a quadruped robot designed and built by a Swiss student team from ETH Zurich and ZHAW Zurich, currently being tested using Automation and Robotics Laboratories (ARL) facilities at our technical centre in the Netherlands. The robot is being used to investigate the potential of ‘dynamic walking’ and jumping to get around in low gravity environments.
SpaceBok could potentially go up to 2 m high in lunar gravity, although such a height poses new challenges. Once it comes off the ground the legged robot needs to stabilise itself to come down again safely – like a mini-spacecraft. So, like a spacecraft. SpaceBok uses a reaction wheel to control its orientation.
[ ESA ]
A new video from GITAI showing progress on their immersive telepresence robot for space.
[ GITAI ]
Tech United’s HERO robot (a Toyota HSR) competed in the RoboCup@Home competition, and it had a couple of garbage-related hiccups.
[ Tech United ]
Even small drones are getting better at autonomous obstacle avoidance in cluttered environments at useful speeds, as this work from the HKUST Aerial Robotics Group shows.
[ HKUST ]
DelFly Nimbles now come in swarms.
[ DelFly Nimble ]
This is a very short video, but it’s a fairly impressive look at a Baxter robot collaboratively helping someone put a shirt on, a useful task for folks with disabilities.
[ Shibata Lab ]
ANYmal can inspect the concrete in sewers for deterioration by sliding its feet along the ground.
[ ETH Zurich ]
HUG is a haptic user interface for teleoperating advanced robotic systems as the humanoid robot Justin or the assistive robotic system EDAN. With its lightweight robot arms, HUG can measure human movements and simultaneously display forces from the distant environment. In addition to such teleoperation applications, HUG serves as a research platform for virtual assembly simulations, rehabilitation, and training.
[ DLR ]
This video about “image understanding” from CMU in 1979 (!) is amazing, and even though it’s long, you won’t regret watching until 3:30. Or maybe you will.
[ ARGOS (pdf) ]
Will Burrard-Lucas’ BeetleCam turned 10 this month, and in this video, he recounts the history of his little robotic camera.
[ BeetleCam ]
In this week’s episode of Robots in Depth, Per speaks with Gabriel Skantze from Furhat Robotics.
Gabriel Skantze is co-founder and Chief Scientist at Furhat Robotics and Professor in speech technology at KTH with a specialization in conversational systems. He has a background in research into how humans use spoken communication to interact.
In this interview, Gabriel talks about how the social robot revolution makes it necessary to communicate with humans in a human ways through speech and facial expressions. This is necessary as we expand the number of people that interact with robots as well as the types of interaction. Gabriel gives us more insight into the many challenges of implementing spoken communication for co-bots, where robots and humans work closely together. They need to communicate about the world, the objects in it and how to handle them. We also get to hear how having an embodied system using the Furhat robot head helps the interaction between humans and the system.
[ Robots in Depth ] Continue reading →
Posted in Human Robots
#435660 Toyota Research Developing New ...
With the Olympics taking place next year in Japan, Toyota is (among other things) stepping up its robotics game to help provide “mobility for all.” We know that Toyota’s HSR will be doing work there, along with a few other mobile systems, but the Toyota Research Institute (TRI) has just announced a new telepresence robot called the T-TR1, featuring an absolutely massive screen designed to give you a near-lifesize virtual presence.
T-TR1 is a virtual mobility/tele-presence robot developed by Toyota Research Institute in the United States. It is equipped with a camera atop a large, near-lifesize display.
By projecting an image of a user from a remote location, the robot will help that person feel more physically present at the robot’s location.
With T-TR1, Toyota will give people that are physically unable to attend the events such as the Games a chance to virtually attend, with an on-screen presence capable of conversation between the two locations.
TRI isn’t ready to share much more detail on this system yet (we asked, of course), but we can infer some things from the video and the rest of the info that’s out there. For example, that ball on top is a 360-degree camera (that looks a lot like an Insta360 Pro), giving the remote user just as good of an awareness of their surroundings as they would if they were there in person. There are multiple 3D-sensing systems, including at least two depth cameras plus a lidar at the base. It’s not at all clear whether the robot is autonomous or semi-autonomous (using the sensors for automated obstacle avoidance, say), and since the woman on the other end of the robot does not seem to be controlling it at all for the demo, it’s hard to make an educated guess about the level of autonomy, or even how it’s supposed to be controlled.
We really like that enormous screen—despite the fact that telepresence now requires pants. It adds to the embodiment that makes independent telepresence robots useful.
We really like that enormous screen—despite the fact that telepresence now requires pants. It adds to the embodiment that makes independent telepresence robots useful. It’s also nice that the robot can move fast enough to keep up a person walking briskly. Hopefully, it’s safe for it to move at that speed in an environment more realistic than a carpeted, half-empty conference room, although it’ll probably have to leverage all of those sensors to do so. The other challenge for the T-TR1 will be bandwidth—even assuming that all of the sensor data processing and stuff is done on-robot, 360 cameras are huge bandwidth hogs, plus there’s the primary (presumably high quality) feed from the main camera, and then the video of the user coming the other way. It’s a lot of data in a very latency-sensitive application, and it’ll presumably be operating in places where connectivity is going to be a challenge due to crowds. This has always been a problem for telepresence robots—no matter how amazing your robot is, the experience will often for better or worse be defined by Internet connections that you may have no control over.
We should emphasize that Toyota has only released the bare minimum of information about the T-TR1, although we’re told that we can expect more as the 2020 Olympics approach: opening ceremonies are one year from today.
[ TRI ] Continue reading →
Posted in Human Robots
#435658 Video Friday: A Two-Armed Robot That ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
Let us know if you have suggestions for next week, and enjoy today’s videos.
I’m sure you’ve seen this video already because you read this blog every day, but if you somehow missed it because you were skiing across Antarctica (the only valid excuse we’re accepting today), here’s our video introducing HMI’s Aquanaut transforming robot submarine.
And after you recover from all that frostbite, make sure and read our in-depth feature article here.
[ Aquanaut ]
Last week we complained about not having seen a ballbot with a manipulator, so Roberto from CMU shared a new video of their ballbot, featuring a pair of 7-DoF arms.
We should learn more at Humanoids 2019.
[ CMU ]
Thanks Roberto!
The FAA is making it easier for recreational drone pilots to get near-realtime approval to fly in lightly controlled airspace.
[ LAANC ]
Self-reconfigurable modular robots are usually composed of multiple modules with uniform docking interfaces that can be transformed into different configurations by themselves. The reconfiguration planning problem is finding what sequence of reconfiguration actions are required for one arrangement of modules to transform into another. We present a novel reconfiguration planning algorithm for modular robots. The algorithm compares the initial configuration with the goal configuration efficiently. The reconfiguration actions can be executed in a distributed manner so that each module can efficiently finish its reconfiguration task which results in a global reconfiguration for the system. In the end, the algorithm is demonstrated on real modular robots and some example reconfiguration tasks are provided.
[ CKbot ]
A nice design of a gripper that uses a passive thumb of sorts to pick up flat objects from flat surfaces.
[ Paper ] via [ Laval University ]
I like this video of a palletizing robot from Kawasaki because in the background you can see a human doing the exact same job and obviously not enjoying it.
[ Kawasaki ]
This robot cleans and “brings joy and laughter.” What else do we need?
I do appreciate that all the robots are named Leo, and that they’re also all female.
[ LionsBot ]
This is less of a dishwashing robot and more of a dishsorting robot, but we’ll forgive it because it doesn’t drop a single dish.
[ TechMagic ]
Thanks Ryosuke!
A slight warning here that the robot in the following video (which costs something like $180,000) appears “naked” in some scenes, none of which are strictly objectionable, we hope.
Beautifully slim and delicate motion life-size motion figures are ideal avatars for expressing emotions to customers in various arts, content and businesses. We can provide a system that integrates not only motion figures but all moving devices.
[ Speecys ]
The best way to operate a Husky with a pair of manipulators on it is to become the robot.
[ UT Austin ]
The FlyJacket drone control system from EPFL has been upgraded so that it can yank you around a little bit.
In several fields of human-machine interaction, haptic guidance has proven to be an effective training tool for enhancing user performance. This work presents the results of psychophysical and motor learning studies that were carried out with human participant to assess the effect of cable-driven haptic guidance for a task involving aerial robotic teleoperation. The guidance system was integrated into an exosuit, called the FlyJacket, that was developed to control drones with torso movements. Results for the Just Noticeable Difference (JND) and from the Stevens Power Law suggest that the perception of force on the users’ torso scales linearly with the amplitude of the force exerted through the cables and the perceived force is close to the magnitude of the stimulus. Motor learning studies reveal that this form of haptic guidance improves user performance in training, but this improvement is not retained when participants are evaluated without guidance.
[ EPFL ]
The SAND Challenge is an opportunity for small businesses to compete in an autonomous unmanned aerial vehicle (UAV) competition to help NASA address safety-critical risks associated with flying UAVs in the national airspace. Set in a post-natural disaster scenario, SAND will push the envelope of aviation.
[ NASA ]
Legged robots have the potential to traverse diverse and rugged terrain. To find a safe and efficient navigation path and to carefully select individual footholds, it is useful to predict properties of the terrain ahead of the robot. In this work, we propose a method to collect data from robot-terrain interaction and associate it to images, to then train a neural network to predict terrain properties from images.
[ RSL ]
Misty wants to be your new receptionist.
[ Misty Robotics ]
For years, we’ve been pointing out that while new Roombas have lots of great features, older Roombas still do a totally decent job of cleaning your floors. This video is a performance comparison between the newest Roomba (the S9+) and the original 2002 Roomba (!), and the results will surprise you. Or maybe they won’t.
[ Vacuum Wars ]
Lex Fridman from MIT interviews Chris Urmson, who was involved in some of the earliest autonomous vehicle projects, Google’s original self-driving car among them, and is currently CEO of Aurora Innovation.
Chris Urmson was the CTO of the Google Self-Driving Car team, a key engineer and leader behind the Carnegie Mellon autonomous vehicle entries in the DARPA grand challenges and the winner of the DARPA urban challenge. Today he is the CEO of Aurora Innovation, an autonomous vehicle software company he started with Sterling Anderson, who was the former director of Tesla Autopilot, and Drew Bagnell, Uber’s former autonomy and perception lead.
[ AI Podcast ]
In this week’s episode of Robots in Depth, Per speaks with Lael Odhner from RightHand Robotics.
Lael Odhner is a co-founder of RightHand Robotics, that is developing a gripper based on the combination of control and soft, compliant parts to get better grasping of objects. Their work focuses on grasping and manipulating everyday human objects in everyday environments.This mimics how human hands combine control and flexibility to grasp objects with great dexterity.
The combination of control and compliance makes the RightHand robotics gripper very light-weight and affordable. The compliance makes it easier to grasp objects of unknown shape and differs from the way industrial robots usually grip. The compliance also helps in a more unstructured environment where contact with the object and its surroundings cannot be exactly predicted.
[ RightHand Robotics ] via [ Robots in Depth ] Continue reading →
Posted in Human Robots
#435648 Surprisingly Speedy Soft Robot Survives ...
Soft robots are getting more and more popular for some very good reasons. Their relative simplicity is one. Their relative low cost is another. And for their simplicity and low cost, they’re generally able to perform very impressively, leveraging the unique features inherent to their design and construction to move themselves and interact with their environment. The other significant reason why soft robots are so appealing is that they’re durable. Without the constraints of rigid parts, they can withstand the sort of abuse that would make any roboticist cringe.
In the current issue of Science Robotics, a group of researchers from Tsinghua University in China and University of California, Berkeley, present a new kind of soft robot that’s both higher performance and much more robust than just about anything we’ve seen before. The deceptively simple robot looks like a bent strip of paper, but it’s able to move at 20 body lengths per second and survive being stomped on by a human wearing tennis shoes. Take that, cockroaches.
This prototype robot measures just 3 centimeters by 1.5 cm. It takes a scanning electron microscope to actually see what the robot is made of—a thermoplastic layer is sandwiched by palladium-gold electrodes, bonded with adhesive silicone to a structural plastic at the bottom. When an AC voltage (as low as 8 volts but typically about 60 volts) is run through the electrodes, the thermoplastic extends and contracts, causing the robot’s back to flex and the little “foot” to shuffle. A complete step cycle takes just 50 milliseconds, yielding a 200 hertz gait. And technically, the robot “runs,” since it does have a brief aerial phase.
Image: Science Robotics
Photos from a high-speed camera show the robot’s gait (A to D) as it contracts and expands its body.
To put the robot’s top speed of 20 body lengths per second in perspective, have a look at this nifty chart, which shows where other animals relative running speeds of some animals and robots versus body mass:
Image: Science Robotics
This chart shows the relative running speeds of some mammals (purple area), arthropods (orange area), and soft robots (blue area) versus body mass. For both mammals and arthropods, relative speeds show a strong negative scaling law with respect to the body mass: speeds increase as body masses decrease. However, for soft robots, the relationship appears to be the opposite: speeds decrease as the body mass decrease. For the little soft robots created by the researchers from Tsinghua University and UC Berkeley (red stars), the scaling law is similar to that of living animals: Higher speed was attained as the body mass decreased.
If you were wondering, like we were, just what that number 39 is on that chart (top left corner), it’s a species of tiny mite that was discovered underneath a rock in California in 1916. The mite is just under 1 mm in size, but it can run at 0.8 kilometer per hour, which is 322 body lengths per second, making it by far (like, by a factor of two at least) the fastest land animal on Earth relative to size. If a human was to run that fast relative to our size, we’d be traveling at a little bit over 2,000 kilometers per hour. It’s not a coincidence that pretty much everything in the upper left of the chart is an insect—speed scales favorably with decreasing mass, since actuators have a proportionally larger effect.
Other notable robots on the chart with impressive speed to mass ratios are number 27, which is this magnetically driven quadruped robot from UMD, and number 86, UC Berkeley’s X2-VelociRoACH.
Anyway, back to this robot. Some other cool things about it:
You can step on it, squishing it flat with a load about 1 million times its own body weight, and it’ll keep on crawling, albeit only half as fast.
Even climbing a slope of 15 degrees, it can still manage to move at 1 body length per second.
It carries peanuts! With a payload of six times its own weight, it moves a sixth as fast, but still, it’s not like you need your peanuts delivered all that quickly anyway, do you?
Image: Science Robotics
The researchers also put together a prototype with two legs instead of one, which was able to demonstrate a potentially faster galloping gait by spending more time in the air. They suggest that robots like these could be used for “environmental exploration, structural inspection, information reconnaissance, and disaster relief,” which are the sorts of things that you suggest that your robot could be used for when you really have no idea what it could be used for. But this work is certainly impressive, with speed and robustness that are largely unmatched by other soft robots. An untethered version seems possible due to the relatively low voltages required to drive the robot, and if they can put some peanut-sized sensors on there as well, practical applications might actually be forthcoming sometime soon.
“Insect-scale Fast Moving and Ultrarobust Soft Robot,” by Yichuan Wu, Justin K. Yim, Jiaming Liang, Zhichun Shao, Mingjing Qi, Junwen Zhong, Zihao Luo, Xiaojun Yan, Min Zhang, Xiaohao Wang, Ronald S. Fearing, Robert J. Full, and Liwei Lin from Tsinghua University and UC Berkeley, is published in Science Robotics. Continue reading →
Posted in Human Robots