Welding Redefined: Unleashing the Power of Robotics for Unrivaled Precision, Efficiency, and Quality

Robotic Welding: A Comprehensive Guide

Grasping objects of different sizes, shapes and textures is a problem that is easy for a human, but challenging for a robot. Researchers from the University of Cambridge designed a soft, 3D printed robotic hand that cannot independently move its fingers but can still carry out a range of complex movements.&nbsp;The robot hand was trained to grasp different objects and was able to predict whether it would drop them by using the information provided from sensors placed on its &lsquo;skin&rsquo;.&nbsp;This type of passive movement makes the robot far easier to control and far more energy-efficient than robots with fully motorised fingers. The researchers say their adaptable design could be used in the development of low-cost robots that are capable of more natural movement and can learn to grasp a wide range of objects. The <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202200390" target="_blank">results</a> are reported in the journal Advanced Intelligent Systems.&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/haWziO6aOqc?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>In the natural world, movement results from the interplay between the brain and the body: this enables people and animals to move in complex ways without expending unnecessary amounts of energy. Over the past several years, soft components have begun to be integrated into robotics design thanks to advances in 3D printing techniques, which have allowed researchers to add complexity to simple, energy-efficient systems.&nbsp;The human hand is highly complex, and recreating all of its dexterity and adaptability in a robot is a massive research challenge. Most of today&rsquo;s advanced robots are not capable of manipulation tasks that small children can perform with ease. For example, humans instinctively know how much force to use when picking up an egg, but for a robot this is a challenge: too much force, and the egg could shatter; too little, and the robot could drop it. In addition, a fully actuated robot hand, with motors for each joint in each finger, requires a significant amount of energy.&nbsp;In <a href="http://www.eng.cam.ac.uk/profiles/fi224" target="_blank">Professor Fumiya&nbsp;</a><a href="http://www.eng.cam.ac.uk/profiles/fi224" target="_blank">Iida</a>&rsquo;s <a href="https://birlab.org/" target="_blank">Bio-Inspired Robotics Laboratory</a> in Cambridge&rsquo;s Department of Engineering, researchers have been developing potential solutions to both problems: a robot hand than can grasp a variety of objects with the correct amount of pressure while using a minimal amount of energy.&nbsp;&ldquo;In <a href="http://www.eng.cam.ac.uk/news/3d-printed-robot-hand-plays-piano" target="_blank">earlier experiments</a>, our lab has shown that it&rsquo;s possible to get a significant range of motion in a robot hand just by moving the wrist,&rdquo; said co-author Dr Thomas George-Thuruthel, who is now based at University College London (UCL) <a href="https://www.ucl.ac.uk/ucl-east/study-and-research/robotics-and-autonomous-systems" target="_blank">East</a>. &ldquo;We wanted to see whether a robot hand based on passive movement could not only grasp objects, but would be able to predict whether it was going to drop the objects or not, and adapt accordingly.&rdquo;&nbsp;The researchers used a 3D-printed anthropomorphic hand implanted with tactile sensors, so that the hand could sense what it was touching. The hand was only capable of passive, wrist-based movement.&nbsp;The team carried out more than 1,200 tests with the robot hand, observing its ability to grasp small objects without dropping them. The robot was initially trained using small 3D printed plastic balls, and grasped them using a pre-defined action obtained through human demonstrations.&nbsp;&ldquo;This kind of hand has a bit of springiness to it: it can pick things up by itself without any actuation of the fingers,&rdquo; said first author Dr Kieran Gilday, who is now based at EPFL in Lausanne, Switzerland. &ldquo;The tactile sensors give the robot a sense of how well the grip is going, so it knows when it&rsquo;s starting to slip. This helps it to predict when things will fail.&rdquo;&nbsp;The robot used trial and error to learn what kind of grip would be successful. After finishing the training with the balls, it then attempted to grasp different objects including a peach, a computer mouse and a roll of bubble wrap. In these tests, the hand was able to successfully grasp 11 of 14 objects.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1684333513339-CENTRE_RobotHand_CREDIT+Bio-Inspired+Robotics+Laboratory%2C+University+of+Cambridge.jpg" style="width: 766px;" class="fr-fic fr-dib">Credit: Bio-Inspired Robotics Laboratory, University of Cambridge.&nbsp;&ldquo;The sensors, which are sort of like the robot&rsquo;s skin, measure the pressure being applied to the object,&rdquo; said Dr George-Thuruthel. &ldquo;We can&rsquo;t say exactly what information the robot is getting, but it can theoretically estimate where the object has been grasped and with how much force.&rdquo;&nbsp;&ldquo;The robot learns that a combination of a particular motion and a particular set of sensor data will lead to failure, which makes it a customisable solution,&rdquo; said Dr Gilday. &ldquo;The hand is very simple, but it can pick up a lot of objects with the same strategy.&rdquo;&nbsp;&ldquo;The big advantage of this design is the range of motion we can get without using any actuators,&rdquo; said Professor Iida. &ldquo;We want to simplify the hand as much as possible. We can get lots of good information and a high degree of control without any actuators, so that when we do add them, we&rsquo;ll get more complex behaviour in a more efficient package.&rdquo;&nbsp;A fully actuated robotic hand, in addition to the amount of energy it requires, is also a complex control problem. The passive design of the Cambridge-designed hand, using a small number of sensors, is easier to control, provides a wide range of motion, and streamlines the learning process.&nbsp;In future, the system could be expanded in several ways, such as by adding computer vision capabilities, or teaching the robot to exploit its environment, which would enable it to grasp a wider range of objects.&nbsp;<hr>Reference: K. Gilday, Dr. T. George-Thuruthel, Prof. F. Iida. &lsquo;<a href="https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202200390" target="_blank">Predictive Learning of Error Recovery with a Sensorised Passivity-based Soft Anthropomorphic Hand</a>.&rsquo; Advanced Intelligent Systems (2023). 10.1002/aisy.202200390&nbsp;

Researchers have designed a low-cost, energy-efficient robotic hand that can grasp a range of objects – and not drop them – using just the movement of its wrist and the feeling in its ‘skin’.  

It's all in the wrist: energy-efficient robot hand learns how not to drop the ball

This article was first published on&nbsp;<a href="https://news.mit.edu/2023/speedy-robo-gripper-reflexively-organizes-spaces-0427" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>. &nbsp;<hr>When manipulating an arcade claw, a player can plan all she wants. But once she presses the joystick button, it&rsquo;s a game of wait-and-see. If the claw misses its target, she&rsquo;ll have to start from scratch for another chance at a prize.The slow and deliberate approach of the arcade claw is similar to state-of-the-art pick-and-place robots, which use high-level planners to process visual images and plan out a series of moves to grab for an object. If a gripper misses its mark, it&rsquo;s back to the starting point, where the controller must map out a new plan. &nbsp;Looking to give robots a more nimble, human-like touch, MIT engineers have now developed <a href="https://biomimetics.mit.edu/research/reflexive-control" target="_blank">a gripper that grasps by reflex</a>. Rather than start from scratch after a failed attempt, the team&rsquo;s robot adapts in the moment to reflexively roll, palm, or pinch an object to get a better hold. It&rsquo;s able to carry out these &ldquo;last centimeter&rdquo; adjustments (a riff on the &ldquo;last mile&rdquo; delivery problem) without engaging a higher-level planner, much like how a person might fumble in the dark for a bedside glass without much conscious thought.The new design is the first to incorporate reflexes into a robotic planning architecture. For now, the system is a proof of concept and provides a general organizational structure for embedding reflexes into a robotic system. Going forward, the researchers plan to program more complex reflexes to enable nimble, adaptable machines that can work with and among humans in ever-changing settings.<iframe width="640" height="360" src="https://www.youtube.com/embed/XxDi-HEpXn4?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>&ldquo;In environments where people live and work, there&rsquo;s always going to be uncertainty,&rdquo; says Andrew SaLoutos, a graduate student in MIT&rsquo;s Department of Mechanical Engineering. &ldquo;Someone could put something new on a desk or move something in the break room or add an extra dish to the sink. We&rsquo;re hoping a robot with reflexes could adapt and work with this kind of uncertainty.&rdquo;SaLoutos and his colleagues will present a <a href="https://arxiv.org/abs/2209.11367" target="_blank">paper</a> on their design in May at the IEEE International Conference on Robotics and Automation (ICRA). His MIT co-authors include postdoc Hongmin Kim, graduate student Elijah Stanger-Jones, Menglong Guo SM &rsquo;22, and professor of mechanical engineering Sangbae Kim, the director of the Biomimetic Robotics Laboratory at MIT.<h2>High and low</h2>Many modern robotic grippers are designed for relatively slow and precise tasks, such as repetitively fitting together the same parts on a a factory assembly line. These systems depend on visual data from onboard cameras; processing that data limits a robot&rsquo;s reaction time, particularly if it needs to recover from a failed grasp.&ldquo;There&rsquo;s no way to short-circuit out and say, oh shoot, I have to do something now and react quickly,&rdquo; SaLoutos says. &ldquo;Their only recourse is just to start again. And that takes a lot of time computationally.&rdquo;In their new work, Kim&rsquo;s team built a more reflexive and reactive platform, using fast, responsive actuators that they originally developed for the group&rsquo;s <a href="https://news.mit.edu/2022/3-questions-how-mit-mini-cheetah-learns-run-fast-0317" target="_blank">mini cheetah</a> &mdash; a nimble, four-legged robot designed to run, leap, and quickly adapt its gait to various types of terrain. &nbsp;The team&rsquo;s design includes a high-speed arm and two lightweight, multijointed fingers. In addition to a camera mounted to the base of the arm, the team incorporated custom high-bandwidth sensors at the fingertips that instantly record the force and location of any contact as well as the proximity of the finger to surrounding objects more than 200 times per second.The researchers designed the robotic system such that a high-level planner initially processes visual data of a scene, marking an object&rsquo;s current location where the gripper should pick the object up, and the location where the robot should place it down. Then, the planner sets a path for the arm to reach out and grasp the object. At this point, the reflexive controller takes over.If the gripper fails to grab hold of the object, rather than back out and start again as most grippers do, the team wrote an algorithm that instructs the robot to quickly act out any of three grasp maneuvers, which they call &ldquo;reflexes,&rdquo; in response to real-time measurements at the fingertips. The three reflexes kick in within the last centimeter of the robot approaching an object and enable the fingers to grab, pinch, or drag an object until it has a better hold.They programmed the reflexes to be carried out without having to involve the high-level planner. Instead, the reflexes are organized at a lower decision-making level, so that they can respond as if by instinct, rather than having to carefully evaluate the situation to plan an optimal fix.&ldquo;It&rsquo;s like how, instead of having the CEO micromanage and plan every single thing in your company, you build a trust system and delegate some tasks to lower-level divisions,&rdquo; Kim says. &ldquo;It may not be optimal, but it helps the company react much more quickly. In many cases, waiting for the optimal solution makes the situation much worse or irrecoverable.&rdquo; &nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1682948812321-MIT_Reflex-Grip-02-PRESS.jpg" style="width: 766px;" class="fr-fic fr-dib">The research team, from left to right: Sangbae Kim, Elijah Stanger-Jones, Andrew SaLoutos, and Hongmin Kim. Image: Jodi Hilton<h2>Cleaning via reflex</h2>The team demonstrated the gripper&rsquo;s reflexes by clearing a cluttered shelf. They set a variety of household objects on a shelf, including a bowl, a cup, a can, an apple, and a bag of coffee grounds. They showed that the robot was able to quickly adapt its grasp to each object&rsquo;s particular shape and, in the case of the coffee grounds, squishiness. Out of 117 attempts, the gripper quickly and successfully picked and placed objects more than 90 percent of the time, without having to back out and start over after a failed grasp.A second experiment showed how the robot could also react in the moment. When researchers shifted a cup&rsquo;s position, the gripper, despite having no visual update of the new location, was able to readjust and essentially feel around until it sensed the cup in its grasp. Compared to a baseline grasping controller, the gripper&rsquo;s reflexes increased the area of successful grasps by over 55 percent.Now, the engineers are working to include more complex reflexes and grasp maneuvers in the system, with a view toward building a general pick-and-place robot capable of adapting to cluttered and constantly changing spaces.&ldquo;Picking up a cup from a clean table &mdash; that specific problem in robotics was solved 30 years ago,&rdquo; Kim notes. &ldquo;But a more general approach, like picking up toys in a toybox, or even a book from a library shelf, has not been solved. Now with reflexes, we think we can one day pick and place in every possible way, so that a robot could potentially clean up the house.&rdquo;This research was supported, in part, by Advanced Robotics Lab of LG Electronics and the Toyota Research Institute.<hr>&quot;Reprinted with permission of&nbsp;<a href="https://news.mit.edu/2023/speedy-robo-gripper-reflexively-organizes-spaces-0427" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>&quot; &nbsp;

MIT researchers (from left): Elijah Stanger-Jones, Hongmin Kim, and Andrew SaLoutos have designed a robot gripper that incorporates reflexes to quickly grasp and sort everyday objects. Image: Jodi Hilton

Rather than start from scratch after a failed attempt, the pick-and-place robot adapts in the moment to get a better hold.

Speedy robo-gripper reflexively organizes cluttered spaces

This article was first published on&nbsp;<a href="https://news.mit.edu/2023/robotic-hand-can-identify-objects-just-one-grasp-0403" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>. &nbsp;<hr>Inspired by the human finger, MIT researchers have developed a robotic hand that uses high-resolution touch sensing to accurately identify an object after grasping it just one time.Many robotic hands pack all their powerful sensors into the fingertips, so an object must be in full contact with those fingertips to be identified, which can take multiple grasps. Other designs use lower-resolution sensors spread along the entire finger, but these don&rsquo;t capture as much detail, so multiple regrasps are often required.Instead, the MIT team built a robotic finger with a rigid skeleton encased in a soft outer layer that has multiple high-resolution sensors incorporated under its transparent &ldquo;skin.&rdquo; The sensors, which use a camera and LEDs to gather visual information about an object&rsquo;s shape, provide continuous sensing along the finger&rsquo;s entire length. Each finger captures rich data on many parts of an object simultaneously.Using this design, the researchers built a three-fingered robotic hand that could identify objects after only one grasp, with about 85 percent accuracy. The rigid skeleton makes the fingers strong enough to pick up a heavy item, such as a drill, while the soft skin enables them to securely grasp a pliable item, like an empty plastic water bottle, without crushing it.These soft-rigid fingers could be especially useful in an at-home-care robot designed to interact with an elderly individual. The robot could lift a heavy item off a shelf with the same hand it uses to help the individual take a bath.&ldquo;Having both soft and rigid elements is very important in any hand, but so is being able to perform great sensing over a really large area, especially if we want to consider doing very complicated manipulation tasks like what our own hands can do. Our goal with this work was to combine all the things that make our human hands so good into a robotic finger that can do tasks other robotic fingers can&rsquo;t currently do,&rdquo; says mechanical engineering graduate student Sandra Liu, co-lead author of a research paper on the robotic finger.Liu wrote the <a data-lf-fd-inspected-kn9eq4roawkarlvp="true" href="https://arxiv.org/pdf/2303.17935.pdf" target="_blank">paper</a> with co-lead author and mechanical engineering undergraduate student Leonardo Zamora Ya&ntilde;ez and her advisor, Edward Adelson, the John and Dorothy Wilson Professor of Vision Science in the Department of Brain and Cognitive Sciences and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). The research will be presented at the RoboSoft Conference.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1680629680887-MIT-GelSignEndoFlex-02-press.jpg" style="width: 766px;" class="fr-fic fr-dib">When the finger grasps an object, the camera captures images as the colored LEDs illuminate the skin from the inside. Using the illuminated contours that appear in the soft skin, an algorithm performs backward calculations to map the contours on the grasped object&rsquo;s surface. Image: Courtesy of the researchers<h2>A human-inspired finger</h2>The robotic finger is comprised of a rigid, 3D-printed endoskeleton that is placed in a mold and encased in a transparent silicone &ldquo;skin.&rdquo; Making the finger in a mold removes the need for fasteners or adhesives to hold the silicone in place.The researchers designed the mold with a curved shape so the robotic fingers are slightly curved when at rest, just like human fingers.&ldquo;Silicone will wrinkle when it bends, so we thought that if we have the finger molded in this curved position, when you curve it more to grasp an object, you won&rsquo;t induce as many wrinkles. Wrinkles are good in some ways &mdash; they can help the finger slide along surfaces very smoothly and easily &mdash; but we didn&rsquo;t want wrinkles that we couldn&rsquo;t control,&rdquo; Liu says.The endoskeleton of each finger contains a pair of detailed touch sensors, known as GelSight sensors, embedded into the top and middle sections, underneath the transparent skin. The sensors are placed so the range of the cameras overlaps slightly, giving the finger continuous sensing along its entire length.The GelSight sensor, based on technology pioneered in the Adelson group, is composed of a camera and three colored LEDs. When the finger grasps an object, the camera captures images as the colored LEDs illuminate the skin from the inside.Using the illuminated contours that appear in the soft skin, an algorithm performs backward calculations to map the contours on the grasped object&rsquo;s surface. The researchers trained a machine-learning model to identify objects using raw camera image data.As they fine-tuned the finger fabrication process, the researchers ran into several obstacles.First, silicone has a tendency to peel off surfaces over time. Liu and her collaborators found they could limit this peeling by adding small curves along the hinges between the joints in the endoskeleton.When the finger bends, the bending of the silicone is distributed along the tiny curves, which reduces stress and prevents peeling. They also added creases to the joints so the silicone is not squashed as much when the finger bends.While troubleshooting their design, the researchers realized wrinkles in the silicone prevent the skin from ripping.&ldquo;The usefulness of the wrinkles was an accidental discovery on our part. When we synthesized them on the surface, we found that they actually made the finger more durable than we expected,&rdquo; she says.<h2>Getting a good grasp</h2>Once they had perfected the design, the researchers built a robotic hand using two fingers arranged in a Y pattern with a third finger as an opposing thumb. The hand captures six images when it grasps an object (two from each finger) and sends those images to a machine-learning algorithm which uses them as inputs to identify the object.Because the hand has tactile sensing covering all of its fingers, it can gather rich tactile data from a single grasp.&ldquo;Although we have a lot of sensing in the fingers, maybe adding a palm with sensing would help it make tactile distinctions even better,&rdquo; Liu says.In the future, the researchers also want to improve the hardware to reduce the amount of wear and tear in the silicone over time and add more actuation to the thumb so it can perform a wider variety of tasks.This work was supported, in part, by the Toyota Research Institute, the Office of Naval Research, and the SINTEF BIFROST project.<hr>&quot;Reprinted with permission of&nbsp;<a href="https://news.mit.edu/2023/robotic-hand-can-identify-objects-just-one-grasp-0403" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>&quot; &nbsp;

MIT researchers developed a soft-rigid robotic finger that incorporates powerful sensors along its entire length, enabling them to produce a robotic hand that could accurately identify objects after only one grasp. Image: Courtesy of the researchers

The three-fingered robotic gripper can “feel” with great sensitivity along the full length of each finger – not just at the tips.

Robotic hand can identify objects with just one grasp

A bird landing on a branch makes the maneuver look like the easiest thing in the world, but in fact, the act of perching involves an extremely delicate balance of timing, high-impact forces, speed, and precision. It&rsquo;s a move so complex that no flapping-wing robot (ornithopter) has been able to master it, until now.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1671502161855-3678x2069.jpg" style="width: 300px;" class="fr-fic fr-dib">&copy; Raphael Zufferey&nbsp;Raphael Zufferey, a postdoctoral fellow in the Laboratory of Intelligent Systems (<a href="https://www.epfl.ch/labs/lis/" target="_blank">LIS</a>) and Biorobotics ab (<a href="https://www.epfl.ch/labs/biorob/" target="_blank">BioRob</a>) in the School of Engineering, is the first author on a recent Nature Communications&nbsp;<a href="https://www.nature.com/articles/s41467-022-35356-5" rel="noopener" target="_blank">paper</a> describing the unique landing gear that makes such perching possible. He built and tested it in collaboration with colleagues at the University of Seville, Spain, where the 700-gram ornithopter itself was developed as part of the European project <a href="https://griffin-erc-advanced-grant.eu/" rel="noopener" target="_blank">GRIFFIN</a>.&ldquo;This is the first phase of a larger project. Once an ornithopter can master landing autonomously on a tree branch, then it has the potential to carry out specific tasks, such as unobtrusively collecting biological samples or measurements from a tree. Eventually, it could even land on artificial structures, which could open up further areas of application,&rdquo; Zufferey says.He adds that the ability to land on a perch could provide a more efficient way for ornithopters &ndash; which, like many unmanned aerial vehicles (UAVs) have limited battery life &ndash; to recharge using solar energy, potentially making them ideal for long-range missions.&ldquo;This is a big step toward using flapping-wing robots, which as of now can really only do free flights, for manipulation tasks and other real-world applications,&rdquo; he says.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1671502227739-1440x836.jpg" style="width: 300px;" class="fr-fic fr-dib"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1671502199234-5472x3648.jpg" style="width: 300px;" class="fr-fic fr-dib">&copy; Raphael Zufferey&nbsp;Maximizing strength and precision; minimizing weight and speedThe engineering problems involved in landing an ornithopter on a perch without any external commands required managing many factors that nature has already so perfectly balanced. The ornithopter had to be able to slow down significantly as it perched, while still maintaining flight. The claw needed to be strong enough to grasp the perch and support the weight of the robot, without being so heavy that it could not be held aloft. &ldquo;That&rsquo;s one reason we went with a single claw rather than two,&rdquo; Zufferey notes. Finally, the robot needed to be able to perceive its environment and the perch in front of it in relation to its own position, speed, and trajectory.The researchers achieved all this by equipping the ornithopter with a fully on-board computer and navigation system, which was complemented by an external motion-capture system to help it determine its position. The ornithopter&rsquo;s leg-claw appendage was finely calibrated to compensate for the up-and-down oscillations of flight as it attempted to hone in on and grasp the perch. The claw itself was designed to absorb the robot&rsquo;s forward momentum upon impact, and to close quickly and firmly to support its weight. Once perched, the robot remains on the perch without energy expenditure.Even with all these factors to consider, Zufferey and his colleagues succeeded, ultimately building not just one but two claw-footed ornithopters to replicate their perching results.Looking ahead, Zufferey is already thinking about how their device could be expanded and improved, especially in an outdoor setting.&ldquo;At the moment, the flight experiments are carried out indoors, because we need to have a controlled flight zone with precise localization from the motion capture system. In the future, we would like to increase the robot&rsquo;s autonomy to perform perching and manipulation tasks outdoors in a more unpredictable environment.&rdquo;<hr>ReferencesZufferey, R., Tormo-Barbero, J., Feliu-Taleg&oacute;n, D. et al. How ornithopters can perch autonomously on a branch. Nat Commun 13, 7713 (2022). https://doi.org/10.1038/s41467-022-35356-5

EPFL researchers have developed a method that allows a flapping-wing robot to land autonomously on a horizontal perch using a claw-like mechanism. The innovation could significantly expand the scope of robot-assisted tasks.

Researchers develop winged robot that can land like a bird

If you&rsquo;ve ever played the claw game at an arcade, you know how hard it is to grab and hold onto objects using robotics grippers. Imagine how much more nerve-wracking that game would be if, instead of plush stuffed animals, you were trying to grab a fragile piece of endangered coral or a priceless artifact from a sunken ship.&nbsp;<iframe src="https://www.youtube.com/embed/SayuM8E_WaQ?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" style="width: 767px; height: 427px;"></iframe>Most of today&rsquo;s robotic grippers rely on embedded sensors, complex feedback loops, or advanced machine learning algorithms, combined with the skill of the operator, to grasp fragile or irregularly shaped objects. But researchers from the <a href="https://seas.harvard.edu/" target="_blank">Harvard John A. Paulson School of Engineering and Applied Sciences&nbsp;</a>(SEAS) have demonstrated an easier way.Taking inspiration from nature, they designed a new type of soft, robotic gripper that uses a collection of thin tentacles to entangle and ensnare objects, similar to how jellyfish collect stunned prey. Alone, individual tentacles, or filaments, are weak. But together, the collection of filaments can grasp and securely hold heavy and oddly shaped objects. The gripper relies on simple inflation to wrap around objects and doesn&rsquo;t require sensing, planning, or feedback control.&nbsp;The research was published in the <a href="https://www.pnas.org/doi/10.1073/pnas.2209819119" target="_blank">Proceedings of the National Academy of Sciences</a> (PNAS).&nbsp;&ldquo;With this research, we wanted to reimagine how we interact with objects,&rdquo; said Kaitlyn Becker, former graduate student and postdoctoral fellow at SEAS and first author of the paper. &ldquo;By taking advantage of the natural compliance of soft robotics and enhancing it with a compliant structure, we designed a gripper that is greater than the sum of its parts and a grasping strategy that can adapt to a range of complex objects with minimal planning and perception.&rdquo;&nbsp;Becker is currently an Assistant Professor of Mechanical Engineering at MIT.&nbsp;The gripper&rsquo;s strength and adaptability come from its ability to entangle itself with the object it is attempting to grasp. The foot-long filaments are hollow, rubber tubes. One side of the tube has thicker rubber than the other, so when the tube is pressurized, it curls like a pigtail or like straightened hair on a rainy day.&nbsp;The curls knot and entangle with each other and the object, with each entanglement increasing the strength of the hold. While the collective hold is strong, each contact is individually weak and won&rsquo;t damage even the most fragile object. To release the object, the filaments are simply depressurized.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjY2NzEyNjkwNTQ5LUdyaXBwZXJfQ2xvc2VVcC5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">A close-up of the gripper&#39;s filaments wrapping around an object. (Credit: Harvard Microrobotics Lab/Harvard SEAS)&nbsp;The researchers used simulations and experiments to test the efficacy of the gripper, picking up a range of objects, including various houseplants and toys. The gripper could be used in real-world applications to grasp soft fruits and vegetables for agricultural production and distribution, delicate tissue in medical settings, even irregularly shaped objects in warehouses, such as glassware.&nbsp;This new approach to grasping combines&nbsp;<a href="https://www.seas.harvard.edu/person/l-mahadevan" target="_blank">Professor L. Mahadevan&rsquo;s</a> research on&nbsp;<a href="https://softmath.seas.harvard.edu/publication/topology-geometry-and-mechanics-of-strongly-stretched-and-twisted-filaments/" target="_blank">the topological mechanics of entangled filaments&nbsp;</a>with&nbsp;<a href="https://seas.harvard.edu/person/robert-wood" target="_blank">Professor Robert Wood&rsquo;s</a> research on&nbsp;<a href="https://www.seas.harvard.edu/news/2019/08/gentle-grip-gelatinous-creatures" target="_blank">soft robotic grippers</a>. &nbsp;&ldquo;Entanglement enables each highly compliant filament to conform locally with a target object leading to a secure but gentle topological grasp that is relatively independent of the details of the nature of the contact,&rdquo; said Mahadevan, the Lola England de Valpine Professor of Applied Mathematics in SEAS, and of Organismic and Evolutionary Biology, and Physics in FAS and co-corresponding author of the paper.&nbsp;&ldquo;This new approach to robotic grasping complements existing solutions by replacing simple, traditional grippers that require complex control strategies with extremely compliant, and morphologically complex filaments that can operate with very simple control,&rdquo; said Wood, the Harry Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences and co-corresponding author of the paper. &ldquo;This approach expands the range of what&rsquo;s possible to pick up with robotic grippers.&rdquo;The research was co-authored by Clark Teeple, Nicholas Charles, Yeonsu Jung, Daniel Baum and James C. Weaver. It was supported in part by the Office of Naval Research, under grant N00014-17-1- 206 and the National Science Foundation under grants EFRI-1830901, DMR-1922321, DMR-2011754, DBI-1556164, and EFMA-1830901, the Simons Foundation, and the Henri Seydoux Fund.

The gripper wrapping around a succulent. (Credit: Harvard Microrobotics Lab/Harvard SEAS)

Jellyfish-like soft gripper mimics the mechanics of curly hair

Tentacle robot can gently grasp fragile objects

Researcher <a href="https://www.linkedin.com/in/idil%C3%B6zdamar/" rel="noopener noreferrer" target="_blank">Idil Ozdamar</a> proposes a new telemanipulation framework that enables both the individual and combined control of any number of robotic arms.&nbsp;Teleoperation is a widely adopted strategy to control robotic manipulators executing complex tasks that require highly dexterous movements and critical high-level intelligence.&nbsp;Classical teleoperation schemes are based on either joystick control, or on more intuitive interfaces which map directly the user arm motions into one robot arm&#39;s motions. These approaches have limits when the execution of a given task requires reconfigurable multiple robotic arm systems.&nbsp;Indeed, the simultaneous teleoperation of two or more robot arms could extend the workspace of the manipulation cell, or increase its total payload, or afford other advantages. In different phases of a reconfigurable multi-arm system, each robot could act as an independent arm, or as one of a pair of cooperating arms, or as one of the fingers of a virtual, large robot hand.&nbsp;This manuscript proposes a novel telemanipulation framework that enables both the individual and combined control of any number of robotic arms. Thanks to the designed control architecture, the human operator can intuitively choose the proposed control modalities and the manipulators that make the task convenient to execute through the user interface.&nbsp;Moreover, through the tele-impedance paradigm, the system can address complex tasks that require physical interaction by letting the robot mimic the arm impedance and position references of the human operator. The proposed framework is validated with 8 subjects controlling &nbsp;4 Franka Emika robots with 7-DoFs to execute a telemanipulation task. Qualitative results of the experiments show us the promising applicability of our framework.Access the full paper <a href="https://www.researchgate.net/publication/362038178_A_Shared_Autonomy_Reconfigurable_Control_Framework_for_Telemanipulation_of_Multi-arm_Systems" rel="noopener noreferrer" target="_blank">here</a>.

Now it is possible to teleoperate individual and combined control of any number of robotic arms. Thanks to the designed control architecture, the human operator can intuitively create robot groups to control them together.


Controlling and Reconfiguring Multiple Collaborative Robot Arms

This article was first published on <a href="https://www.csail.mit.edu/news/flexible-way-grab-items-feeling" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>. &nbsp;<hr>The notion of a large metallic robot that speaks in monotone and moves in lumbering, deliberate steps is somewhat hard to shake. But practitioners in the field of soft robotics have an entirely different image in mind &mdash; autonomous devices composed of compliant parts that are gentle to the touch, more closely resembling human fingers than R2-D2 or Robby the Robot.That model is now being pursued by Professor Edward Adelson and his Perceptual Science Group at MIT&rsquo;s Computer Science and Artificial Intelligence Laboratory (CSAIL). In a&nbsp;<a href="https://arxiv.org/abs/2204.07146" target="_blank">recent project</a>, Adelson and Sandra Liu &mdash; a mechanical engineering PhD student at CSAIL &mdash; have developed a robotic gripper using novel &ldquo;GelSight Fin Ray&rdquo; fingers that, like the human hand, is supple enough to manipulate objects. What sets this work apart from other efforts in the field is that Liu and Adelson have endowed their gripper with touch sensors that can meet or exceed the sensitivity of human skin.Their <a href="https://arxiv.org/abs/2204.07146" target="_blank">work was presented</a> last week at the 2022 IEEE 5th International Conference on Soft Robotics.<iframe src="https://www.youtube.com/embed/rvezSGdFPx0?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" style="width: 764px; height: 428px;"></iframe>The fin ray has become a popular item in soft robotics owing to a discovery made in 1997 by the German biologist Leif Kniese. He noticed that when he pushed against a fish&rsquo;s tail with his finger, the ray would bend toward the applied force, almost embracing his finger, rather than tilting away. The design has become popular, but it lacks tactile sensitivity. &ldquo;It&rsquo;s versatile because it can passively adapt to different shapes and therefore grasp a variety of objects,&rdquo; Liu explains. &ldquo;But in order to go beyond what others in the field had already done, we set out to incorporate a rich tactile sensor into our gripper.&rdquo;The gripper consists of two flexible fin ray fingers that conform to the shape of the object they come in contact with. The fingers themselves are assembled from flexible plastic materials made on a 3D printer, which is pretty standard in the field. However, the fingers typically used in soft robotic grippers have supportive cross-struts running through the length of their interiors, whereas Liu and Adelson hollowed out the interior region so they could create room for their camera and other sensory components.The camera is mounted to a semirigid backing on one end of the hollowed-out cavity, which is, itself, illuminated by LEDs. The camera faces a layer of &ldquo;sensory&rdquo; pads composed of silicone gel (known as &ldquo;GelSight&rdquo;) that is glued to a thin layer of acrylic material. The acrylic sheet, in turn, is attached to the plastic finger piece at the opposite end of the inner cavity. Upon touching an object, the finger will seamlessly fold around it, melding to the object&rsquo;s contours. By determining exactly how the silicone and acrylic sheets are deformed during this interaction, the camera &mdash; along with accompanying computational algorithms &mdash; can assess the general shape of the object, its surface roughness, its orientation in space, and the force being applied by (and imparted to) each finger.Liu and Adelson tested out their gripper in an experiment during which just one of the two fingers was &ldquo;sensorized.&rdquo; Their device successfully handled such items as a mini-screwdriver, a plastic strawberry, an acrylic paint tube, a Ball Mason jar, and a wine glass. While the gripper was holding the fake strawberry, for instance, the internal sensor was able to detect the &ldquo;seeds&rdquo; on its surface. The fingers grabbed the paint tube without squeezing so hard as to breach the container and spill its contents.The GelSight sensor could even make out the lettering on the Mason jar, and did so in a rather clever way. The overall shape of the jar was ascertained first by seeing how the acrylic sheet was bent when wrapped around it. That pattern was then subtracted, by a computer algorithm, from the deformation of the silicone pad, and what was left was the more subtle deformation due just to the letters.Glass objects are challenging for vision-based robots because of the refraction of the light. Tactile sensors are immune to such optical ambiguity. When the gripper picked up the wine glass, it could feel the orientation of the stem and could make sure the glass was pointing straight up before it was slowly lowered. When the base touched the tabletop, the gel pad sensed the contact. Proper placement occurred in seven out of 10 trials and, thankfully, no glass was harmed during the filming of this experiment.Wenzhen Yuan, an assistant professor in the Robotics Institute at Carnegie Mellon University who was not invovled with the research, says, &ldquo;Sensing with soft robots has been a big challenge, because it is difficult to set up sensors &mdash; which are traditionally rigid &mdash; on soft bodies,&rdquo; Yuan says. &ldquo;This paper provides a neat solution to that problem. The authors used a very smart design to make their vision-based sensor work for the compliant gripper, in this way generating very good results when robots grasp objects or interact with the external environment. The technology has lots of potential to be widely used for robotic grippers in real-world environments.&rdquo;Liu and Adelson can foresee many possible applications for the GelSight Fin Ray, but they are first contemplating some improvements. By hollowing out the finger to clear space for their sensory system, they introduced a structural instability, a tendency to twist, that they believe can be counteracted through better design. They want to make GelSight sensors that are compatible with soft robots devised by other research teams. And they also plan to develop a three-fingered gripper that could be useful in such tasks as picking up pieces of fruit and evaluating their ripeness.Tactile sensing, in their approach, is based on inexpensive components: a camera, some gel, and some LEDs. Liu hopes that with a technology like GelSight, &ldquo;it may be possible to come up with sensors that are both practical and affordable.&rdquo; That, at least, is one goal that she and others in the lab are striving toward.<hr>&quot;Reprinted with permission of&nbsp;<a href="https://www.csail.mit.edu/news/flexible-way-grab-items-feeling" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>&quot;&nbsp;

In a recent project, Professor Edward Adelson and Sandra Liu — a mechanical engineering PhD student at CSAIL — have developed a robotic gripper using novel “GelSight Fin Ray” fingers that, like the human hand, is supple enough to manipulate objects.

A flexible way to grab items with feeling

<h2 id="isPasted">The Right Tool For The Job</h2>The end-of-arm tooling (EOAT) is one of the most important parts of your robot system. The EOAT spends the most time interacting directly with your parts and a well-designed tool/part interface can save both time and effort when programming a task that requires precision.There are different types of EOATs for different tasks. With its plug-and-play approach, the Forge/Ctrl makes it easy to attach and swap between a variety of EOATs, ensuring that you have the flexibility you need to optimize your task.Out of the box, Forge/OS supports several types of gripper EOATs:<ul><li>Electric and pneumatic multi-finger grippers</li><li>Pneumatically actuated magnetic grippers</li><li>Suction grippers</li></ul>Each of these types of grippers has its own benefits and drawbacks. For example, suction grippers come in a wide variety of sizes and material applications but usually require a flat and non-porous surface for best results. Magnetic grippers are very powerful but have limited material applications. Multi-finger grippers can provide precise placement but sometimes require extra fixturing for parts presentation. This document provides information to help you learn how each type of gripper can best be used.<h2>Electric and pneumatic multi-finger grippers</h2>Multi-finger grippers most commonly come in two types: two-finger grippers and three-finger grippers. Two-finger grippers (or parallel grippers) have two fingers that open and close along a single axis. Three-finger grippers (or centric grippers) have three fingers that open and close around a center point.Multi-finger grippers are ideal for tasks that require a lot of grip strength and repeatability is a major factor. Because these grippers are often large and require plenty of clearance for grabbing parts and introducing them to a machine, parts must be presented individually, like in a grid or auto-feeder, so the gripper can access a single part without colliding into other parts or objects.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1644539546005-pasted-image-0-7.webp" style="width: 766px;" class="fr-fic fr-dib">Both parallel and centric grippers often come with machineable or replaceable fingers, allowing you to customize the fingers to suit your task. Taking advantage of this customization capability can reduce the need for precise fixturing in part presentation. For example, you can machine the fingers to have a flat interior surface that presses against the top of the part. Using this surface in conjunction with a force sensor allows you to program a motion that picks up the parts by bottoming the part against the interior surface of the gripper finger, meaning parts of varying height will always be positioned in the same place in the gripper.<h2>Magnetic grippers</h2>Pneumatically actuated magnetic grippers provide superior strength and rigidity in applications containing iron (ferrous) materials. Magnetic grippers designed for EOAT applications often have a low-profile magnetic field, enabling the gripper to pick parts from a stack without disturbing any parts below the top of the stack.Despite the limited material applications of magnetic grippers, it’s worth taking advantage of their strength and repeatability. Magnetic grippers are good for applications where the robot arm may need to hold the part in place while it is being processed. They also work well in applications that seem suited for suction grippers but require more grip strength due to the high weight of ferrous materials.Pneumatically actuated magnetic grippers use an air supply to activate or deactivate the magnetic field by moving the magnet toward or away from the work surface of the gripper. Based on the manufacturer of the gripper, some magnetic grippers will be activated when air is applied, while others will be deactivated when air is applied.<h2>Suction grippers</h2>Suction grippers use the flow of air to create a negative pressure area inside of a suction cup. Based on the amount of airflow, suction can be increased or decreased. However, the versatility of suction gripping doesn’t come from the suction force but from the variety and flexibility of suction cups.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1644539564001-pasted-image-0-8.webp" style="width: 766px;" class="fr-fic fr-dib">Suction grippers are ideal for tasks where precision is not needed or else is handled by other means, such as gravity-feed trays or alternative alignment surfaces. Suction grippers are also great for applications where parts have unconventional geometries and require a custom EOAT.Many companies such as Piab and Schmalz make a wide array of suction cups for different applications. Cups may have a low-profile rubber interior for added grip against oily sheet metal or extra bellows and surface flexibility to increase contact against porous cardboard. Selecting the appropriate suction cup can mean the difference between a strong, repeatable grip and plenty of frustration with missed grabs.Because the Forge/Ctrl does not include an internal vacuum generator, the negative pressure inside a suction gripper is created through a generator on the EOAT. Generators can either be mounted directly above the suction cup or inline with the air supply. Direct generators are larger but generate more suction than inline generators. Inline generators enable much greater flexibility in designing custom gripping tools, such as low-profile gripping heads for tight spaces.

The end-of-arm tooling (EOAT) is one of the most important parts of your robot system. The EOAT spends the most time interacting directly with your parts and a well-designed tool/part interface can save both time and effort when programming a task that requires precision.

robotic hands and grippers