Tag Archives: feedback

#437608 Video Friday: Agility Robotics Raises ...

Posted on November 21, 2020 by Android

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!):

IROS 2020 – October 25-29, 2020 – [Online]
ROS World 2020 – November 12, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

Digit is now in full commercial production and we’re excited to announce a $20M funding rounding round co-led by DCVC and Playground Global!

Digits for everyone!

[ Agility Robotics ]

A flexible rover that has both ability to travel long distances and rappel down hard-to-reach areas of scientific interest has undergone a field test in the Mojave Desert in California to showcase its versatility. Composed of two Axel robots, DuAxel is designed to explore crater walls, pits, scarps, vents and other extreme terrain on the moon, Mars and beyond.

This technology demonstration developed at NASA’s Jet Propulsion Laboratory in Southern California showcases the robot’s ability to split in two and send one of its halves — a two-wheeled Axle robot — over an otherwise inaccessible slope, using a tether as support and to supply power.

The rappelling Axel can then autonomously seek out areas to study, safely overcome slopes and rocky obstacles, and then return to dock with its other half before driving to another destination. Although the rover doesn’t yet have a mission, key technologies are being developed that might, one day, help us explore the rocky planets and moons throughout the solar system.

[ JPL ]

A rectangular robot as tiny as a few human hairs can travel throughout a colon by doing back flips, Purdue University engineers have demonstrated in live animal models. Why the back flips? Because the goal is to use these robots to transport drugs in humans, whose colons and other organs have rough terrain. Side flips work, too. Why a back-flipping robot to transport drugs? Getting a drug directly to its target site could remove side effects, such as hair loss or stomach bleeding, that the drug may otherwise cause by interacting with other organs along the way.

[ Purdue ]

This video shows the latest results in the whole-body locomotion control of the humanoid robot iCub achieved by the Dynamic Interaction Control line at IIT-Istituto Italiano di Tecnologia in Genova (Italy). In particular, the iCub now keeps the balance while walking and receiving pushes from an external user. The implemented control algorithms also ensure the robot to remain compliant during locomotion and human-robot interaction, a fundamental property to lower the possibility to harm humans that share the robot surrounding environment.

This is super impressive, considering that iCub was only able to crawl and was still tethered not too long ago. Also, it seems to be blinking properly now, so it doesn’t look like it’s always sleepy.

[ IIT ]

This video shows a set of new tests we performed on Bolt. We conducted tests on 5 different scenarios, 1) walking forward/backward 2) uneven surface 3) soft surface 4) push recovery 5) slippage recovery. Thanks to our feedback control based on Model Predictive Control, the robot can perform walking in the presence of all these uncertainties. We will open-source all the codes in a near future.

[ ODRI ]

The title of this video is “Can you throw your robot into a lake?” The title of this video should be, “Can you throw your robot into a lake and drive it out again?”

[ Norlab ]

AeroVironment Successfully Completes Sunglider Solar HAPS Stratospheric Test Flight, Surpassing 60,000 Feet Altitude and Demonstrating Broadband Mobile Connectivity.

[ AeroVironment ]

We present CoVR, a novel robotic interface providing strong kinesthetic feedback (100 N) in a room-scale VR arena. It consists of a physical column mounted on a 2D Cartesian ceiling robot (XY displacements) with the capacity of (1) resisting to body-scaled users actions such as pushing or leaning; (2) acting on the users by pulling or transporting them as well as (3) carrying multiple potentially heavy objects (up to 80kg) that users can freely manipulate or make interact with each other.

[ DeepAI ]

In a new video, personnel from Swiss energy supply company Kraftwerke Oberhasli AG (KWO) explain how they were able to keep employees out of harm’s way by using Flyability’s Elios 2 to collect visual data while building a new dam.

[ Flyability ]

Enjoy our Ascento robot fail compilation! With every failure we experience, we learn more and we can improve our robot for its next iteration, which will come soon… Stay tuned for more!

FYI posting a robot fails video will pretty much guarantee you a spot in Video Friday!

[ Ascento ]

Humans are remarkably good at using chopsticks. The Guinness World Record witnessed a person using chopsticks to pick up 65 M&Ms in just a minute. We aim to collect demonstrations from humans and to teach robot to use chopsticks.

[ UW Personal Robotics Lab ]

A surprising amount of personality from these Yaskawa assembly robots.

[ Yaskawa ]

This paper presents the system design, modeling, and control of the Aerial Robotic Chain Manipulator. This new robot design offers the potential to exert strong forces and moments to the environment, carry and lift significant payloads, and simultaneously navigate through narrow corridors. The presented experimental studies include a valve rotation task, a pick-and-release task, and the verification of load oscillation suppression to demonstrate the stability and performance of the system.

[ ARL ]

Whether animals or plants, whether in the water, on land or in the air, nature provides the model for many technical innovations and inventions. This is summed up in the term bionics, which is a combination of the words ‘biology‘ and ‘electronics’. At Festo, learning from nature has a long history, as our Bionic Learning Network is based on using nature as the source for future technologies like robots, assistance systems or drive solutions.

[ Festo ]

Dogs! Selfies! Thousands of LEGO bricks! This video has it all.

[ LEGO ]

An IROS workshop talk on “Cassie and Mini Cheetah Autonomy” by Maani Ghaffari and Jessy Grizzle from the University of Michigan.

[ Michigan Robotics ]

David Schaefer’s Cozmo robots are back with this mind-blowing dance-off!

What you just saw represents hundreds of hours of work, David tells us: “I wrote over 10,000 lines of code to create the dance performance as I had to translate the beats per minute of the song into motor rotations in order to get the right precision needed to make the moves look sharp. The most challenging move was the SpongeBob SquareDance as any misstep would send the Cozmos crashing into each other. LOL! Fortunately for me, Cozmo robots are pretty resilient.”

[ Life with Cozmo ]

Thanks David!

This week’s GRASP on Robotics seminar is by Sangbae Kim from MIT, on “Robots with Physical Intelligence.”

While industrial robots are effective in repetitive, precise kinematic tasks in factories, the design and control of these robots are not suited for physically interactive performance that humans do easily. These tasks require ‘physical intelligence’ through complex dynamic interactions with environments whereas conventional robots are designed primarily for position control. In order to develop a robot with ‘physical intelligence’, we first need a new type of machines that allow dynamic interactions. This talk will discuss how the new design paradigm allows dynamic interactive tasks. As an embodiment of such a robot design paradigm, the latest version of the MIT Cheetah robots and force-feedback teleoperation arms will be presented.

[ GRASP ]

This week’s CMU Ri Seminar is by Kevin Lynch from Northwestern, on “Robotics and Biosystems.”

Research at the Center for Robotics and Biosystems at Northwestern University encompasses bio-inspiration, neuromechanics, human-machine systems, and swarm robotics, among other topics. In this talk I will give an overview of some of our recent work on in-hand manipulation, robot locomotion on yielding ground, and human-robot systems.

[ CMU RI ] Continue reading →

Posted in Human Robots

#437598 Video Friday: Sarcos Is Developing a New ...

Posted on November 20, 2020 by Android

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!):

IROS 2020 – October 25-29, 2020 – [Online]
ROS World 2020 – November 12, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today's videos.

NASA’s Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx) spacecraft unfurled its robotic arm Oct. 20, 2020, and in a first for the agency, briefly touched an asteroid to collect dust and pebbles from the surface for delivery to Earth in 2023.

[ NASA ]

New from David Zarrouk’s lab at BGU is AmphiSTAR, which Zarrouk describes as “a kind of a ground-water drone inspired by the cockroaches (sprawling) and by the Basilisk lizard (running over water). The robot hovers due to the collision of its propellers with the water (hydrodynamics not aerodynamics). The robot can crawl and swim at high and low speeds and smoothly transition between the two. It can reach 3.5 m/s on ground and 1.5m/s in water.”

AmphiSTAR will be presented at IROS, starting next week!

[ BGU ]

This is unfortunately not a great video of a video that was taken at a SoftBank Hawks baseball game in Japan last week, but it’s showing an Atlas robot doing an honestly kind of impressive dance routine to support the team.

ロボット応援団に人型ロボット『ATLAS』がアメリカからリモートで緊急参戦！！！
ホークスビジョンの映像をお楽しみ下さい♪#sbhawks #Pepper #spot pic.twitter.com/6aTYn8GGli
— 福岡ソフトバンクホークス（公式） (@HAWKS_official)
October 16, 2020

Editor’s Note: The tweet embed above is not working for some reason—see the video here.

[ SoftBank Hawks ]

Thanks Thomas!

Sarcos is working on a new robot, which looks to be the torso of their powered exoskeleton with the human relocated somewhere else.

[ Sarcos ]

The biggest holiday of the year, International Sloth Day, was on Tuesday! To celebrate, here’s Slothbot!

[ NSF ]

This is one of those simple-seeming tasks that are really difficult for robots.

I love self-resetting training environments.

[ MIT CSAIL ]

The Chiel lab collaborates with engineers at the Center for Biologically Inspired Robotics Research at Case Western Reserve University to design novel worm-like robots that have potential applications in search-and-rescue missions, endoscopic medicine, or other scenarios requiring navigation through narrow spaces.

[ Case Western ]

ANYbotics partnered with Losinger Marazzi to explore ANYmal’s potential of patrolling construction sites to identify and report safety issues. With such a complex environment, only a robot designed to navigate difficult terrain is able to bring digitalization to such a physically demanding industry.

[ ANYbotics ]

Happy 2018 Halloween from Clearpath Robotics!

[ Clearpath ]

Overcoming illumination variance is a critical factor in vision-based navigation. Existing methods tackled this radical illumination variance issue by proposing camera control or high dynamic range (HDR) image fusion. Despite these efforts, we have found that the vision-based approaches still suffer from overcoming darkness. This paper presents real-time image synthesizing from carefully controlled seed low dynamic range (LDR) image, to enable visual simultaneous localization and mapping (SLAM) in an extremely dark environment (less than 10 lux).

[ KAIST ]

What can MoveIt do? Who knows! Let's find out!

[ MoveIt ]

Thanks Dave!

Here we pick a cube from a starting point, manipulate it within the hand, and then put it back. To explore the capabilities of the hand, no sensors were used in this demonstration. The RBO Hand 3 uses soft pneumatic actuators made of silicone. The softness imparts considerable robustness against variations in object pose and size. This lets us design manipulation funnels that work reliably without needing sensor feedback. We take advantage of this reliability to chain these funnels into more complex multi-step manipulation plans.

[ TU Berlin ]

If this was a real solar array, King Louie would have totally cleaned it. Mostly.

[ BYU ]

Autonomous exploration is a fundamental problem for various applications of unmanned aerial vehicles(UAVs). Existing methods, however, were demonstrated to have low efficiency, due to the lack of optimality consideration, conservative motion plans and low decision frequencies. In this paper, we propose FUEL, a hierarchical framework that can support Fast UAV ExpLoration in complex unknown environments.

[ HKUST ]

Countless precise repetitions? This is the perfect task for a robot, thought researchers at the University of Liverpool in the Department of Chemistry, and without further ado they developed an automation solution that can carry out and monitor research tasks, making autonomous decisions about what to do next.

[ Kuka ]

This video shows a demonstration of central results of the SecondHands project. In the context of maintenance and repair tasks, in warehouse environments, the collaborative humanoid robot ARMAR-6 demonstrates a number of cognitive and sensorimotor abilities such as 1) recognition of the need of help based on speech, force, haptics and visual scene and action interpretation, 2) collaborative bimanual manipulation of large objects, 3) compliant mobile manipulation, 4) grasping known and unknown objects and tools, 5) human-robot interaction (object and tool handover) 6) natural dialog and 7) force predictive control.

[ SecondHands ]

In celebration of Ada Lovelace Day, Silicon Valley Robotics hosted a panel of Women in Robotics.

[ Robohub ]

As part of the upcoming virtual IROS conference, HEBI robotics is putting together a tutorial on robotics actuation. While I’m sure HEBI would like you to take a long look at their own actuators, we’ve been assured that no matter what kind of actuators you use, this tutorial will still be informative and useful.

[ YouTube ] via [ HEBI Robotics ]

Thanks Dave!

This week’s UMD Lockheed Martin Robotics Seminar comes from Julie Shah at MIT, on “Enhancing Human Capability with Intelligent Machine Teammates.”

Every team has top performers- people who excel at working in a team to find the right solutions in complex, difficult situations. These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it. Similarly, even when a machine can do the job better than most of us, it can’t explain how. In this talk I share recent work investigating effective ways to blend the unique decision-making strengths of humans and machines. I discuss the development of computational models that enable machines to efficiently infer the mental state of human teammates and thereby collaborate with people in richer, more flexible ways.

[ UMD ]

Matthew Piccoli gives a talk to the UPenn GRASP Lab on “Trading Complexities: Smart Motors and Dumb Vehicles.”

We will discuss my research journey through Penn making the world's smallest, simplest flying vehicles, and in parallel making the most complex brushless motors. What do they have in common? We'll touch on why the quadrotor went from an obscure type of helicopter to the current ubiquitous drone. Finally, we'll get into my life after Penn and what tools I'm creating to further drone and robot designs of the future.

[ UPenn ] Continue reading →

Posted in Human Robots

#437575 AI-Directed Robotic Hand Learns How to ...

Posted on November 19, 2020 by Android

Reaching for a nearby object seems like a mindless task, but the action requires a sophisticated neural network that took humans millions of years to evolve. Now, robots are acquiring that same ability using artificial neural networks. In a recent study, a robotic hand “learns” to pick up objects of different shapes and hardness using three different grasping motions.

The key to this development is something called a spiking neuron. Like real neurons in the brain, artificial neurons in a spiking neural network (SNN) fire together to encode and process temporal information. Researchers study SNNs because this approach may yield insights into how biological neural networks function, including our own.

“The programming of humanoid or bio-inspired robots is complex,” says Juan Camilo Vasquez Tieck, a research scientist at FZI Forschungszentrum Informatik in Karlsruhe, Germany. “And classical robotics programming methods are not always suitable to take advantage of their capabilities.”

Conventional robotic systems must perform extensive calculations, Tieck says, to track trajectories and grasp objects. But a robotic system like Tieck’s, which relies on a SNN, first trains its neural net to better model system and object motions. After which it grasps items more autonomously—by adapting to the motion in real-time.

The new robotic system by Tieck and his colleagues uses an existing robotic hand, called a Schunk SVH 5-finger hand, which has the same number of fingers and joints as a human hand.

The researchers incorporated a SNN into their system, which is divided into several sub-networks. One sub-network controls each finger individually, either flexing or extending the finger. Another concerns each type of grasping movement, for example whether the robotic hand will need to do a pinching, spherical or cylindrical movement.

For each finger, a neural circuit detects contact with an object using the currents of the motors and the velocity of the joints. When contact with an object is detected, a controller is activated to regulate how much force the finger exerts.

“This way, the movements of generic grasping motions are adapted to objects with different shapes, stiffness and sizes,” says Tieck. The system can also adapt its grasping motion quickly if the object moves or deforms.

The robotic grasping system is described in a study published October 24 in IEEE Robotics and Automation Letters. The researchers’ robotic hand used its three different grasping motions on objects without knowing their properties. Target objects included a plastic bottle, a soft ball, a tennis ball, a sponge, a rubber duck, different balloons, a pen, and a tissue pack. The researchers found, for one, that pinching motions required more precision than cylindrical or spherical grasping motions.

“For this approach, the next step is to incorporate visual information from event-based cameras and integrate arm motion with SNNs,” says Tieck. “Additionally, we would like to extend the hand with haptic sensors.”

The long-term goal, he says, is to develop “a system that can perform grasping similar to humans, without intensive planning for contact points or intense stability analysis, and [that is] able to adapt to different objects using visual and haptic feedback.” Continue reading →

Posted in Human Robots

#437571 Video Friday: Snugglebot Is What We All ...

Posted on November 18, 2020 by Android

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!):

IROS 2020 – October 25-25, 2020 – [Online]
Robotica 2020 – November 10-14, 2020 – [Online]
ROS World 2020 – November 12, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Bay Area Robotics Symposium – November 20, 2020 – [Online]
Let us know if you have suggestions for next week, and enjoy today's videos.

Snugglebot is what we all need right now.

[ Snugglebot ]

In his video message on his prayer intention for November, Pope Francis emphasizes that progress in robotics and artificial intelligence (AI) be oriented “towards respecting the dignity of the person and of Creation”.

[ Vatican News ]

KaPOW!

Apparently it's supposed to do that—the disruptor flies off backwards to reduce recoil on the robot, and has its own parachute to keep it from going too far.

[ Ghost Robotics ]

Animals have many muscles, receptors, and neurons which compose feedback loops. In this study, we designed artificial muscles, receptors, and neurons without any microprocessors, or software-based controllers. We imitate the reflexive rule observed in walking experiments of cats, as a result, the Pneumatic Brainless Robot II emerged running motion (a leg trajectory and a gait pattern) through the interaction between the body, the ground, and the artificial reflexes. We envision that the simple reflex circuit we discovered will be a candidate for a minimal model for describing the principles of animal locomotion.

Find the paper, “Brainless Running: A Quasi-quadruped Robot with Decentralized Spinal Reflexes by Solely Mechanical Devices,” on IROS On-Demand.

[ IROS ]

Thanks Yoichi!

I have no idea what these guys are saying, but they're talking about robots that serve chocolate!

The world of experience of the Zotter Schokoladen Manufaktur of managing director Josef Zotter counts more than 270,000 visitors annually. Since March 2019, this world of chocolate in Bergl near Riegersburg in Austria has been enriched by a new attraction: the world's first chocolate and praline robot from KUKA delights young and old alike and serves up chocolate and pralines to guests according to their personal taste.

[ Zotter ]

This paper proposes a systematic solution that uses an unmanned aerial vehicle (UAV) to aggressively and safely track an agile target. The solution properly handles the challenging situations where the intent of the target and the dense environments are unknown to the UAV. The proposed solution is integrated into an onboard quadrotor system. We fully test the system in challenging real-world tracking missions. Moreover, benchmark comparisons validate that the proposed method surpasses the cutting-edge methods on time efficiency and tracking effectiveness.

[ FAST Lab ]

Southwest Research Institute developed a cable management system for collaborative robotics, or “cobots.” Dress packs used on cobots can create problems when cables are too tight (e-stops) or loose (tangling). SwRI developed ADDRESS, or the Adaptive DRESing System, to provide smarter cobot dress packs that address e-stops and tangling.

[ SWRI ]

A quick demonstration of the acoustic contact sensor in the RBO Hand 2. An embedded microphone records the sound inside of the pneumatic finger. Depending on which part of the finger makes contact, the sound is a little bit different. We create a sensor that recognizes these small changes and predicts the contact location from the sound. The visualization on the left shows the recorded sound (top) and which of the nine contact classes the sensor is currently predicting (bottom).

[ TU Berlin ]

The MAVLab won the prize for the “most innovative design” in the IMAV 2018 indoor competition, in which drones had to fly through windows, gates, and follow a predetermined flight path. The prize was awarded for the demonstration of a fully autonomous version of the “DelFly Nimble”, a tailless flapping wing drone.

In order to fly by itself, the DelFly Nimble was equipped with a single, small camera and a small processor allowing onboard vision processing and control. The jury of international experts in the field praised the agility and autonomous flight capabilities of the DelFly Nimble.

[ MAVLab ]

A reactive walking controller for the Open Dynamic Robot Initiative's skinny quadruped.

[ ODRI ]

Mobile service robots are already able to recognize people and objects while navigating autonomously through their operating environments. But what is the ideal position of the robot to interact with a user? To solve this problem, Fraunhofer IPA developed an approach that connects navigation, 3D environment modeling, and person detection to find the optimal goal pose for HRI.

[ Fraunhofer ]

Yaskawa has been in robotics for a very, very long time.

[ Yaskawa ]

Black in Robotics IROS launch event, featuring Carlotta Berry.

[ Black in Robotics ]

What is AI? I have no idea! But these folks have some opinions.

[ MIT ]

Aerial-based Observations of Volcanic Emissions (ABOVE) is an international collaborative project that is changing the way we sample volcanic gas emissions. Harnessing recent advances in drone technology, unoccupied aerial systems (UAS) in the ABOVE fleet are able to acquire aerial measurements of volcanic gases directly from within previously inaccessible volcanic plumes. In May 2019, a team of 30 researchers undertook an ambitious field deployment to two volcanoes – Tavurvur (Rabaul) and Manam in Papua New Guinea – both amongst the most prodigious emitters of sulphur dioxide on Earth, and yet lacking any measurements of how much carbon they emit to the atmosphere.

[ ABOVE ]

A talk from IHMC's Robert Griffin for ICCAS 2020, including a few updates on their Nadia humanoid.

[ IHMC ] Continue reading →

Posted in Human Robots

#437543 This Is How We’ll Engineer Artificial ...

Posted on November 17, 2020 by Android

Take a Jeopardy! guess: this body part was once referred to as the “consummation of all perfection as an instrument.”

Answer: “What is the human hand?”

Our hands are insanely complex feats of evolutionary engineering. Densely-packed sensors provide intricate and ultra-sensitive feelings of touch. Dozens of joints synergize to give us remarkable dexterity. A “sixth sense” awareness of where our hands are in space connects them to the mind, making it possible to open a door, pick up a mug, and pour coffee in total darkness based solely on what they feel.

So why can’t robots do the same?

In a new article in Science, Dr. Subramanian Sundaram at Boston and Harvard University argues that it’s high time to rethink robotic touch. Scientists have long dreamed of artificially engineering robotic hands with the same dexterity and feedback that we have. Now, after decades, we’re at the precipice of a breakthrough thanks to two major advances. One, we better understand how touch works in humans. Two, we have the mega computational powerhouse called machine learning to recapitulate biology in silicon.

Robotic hands with a sense of touch—and the AI brain to match it—could overhaul our idea of robots. Rather than charming, if somewhat clumsy, novelties, robots equipped with human-like hands are far more capable of routine tasks—making food, folding laundry—and specialized missions like surgery or rescue. But machines aren’t the only ones to gain. For humans, robotic prosthetic hands equipped with accurate, sensitive, and high-resolution artificial touch is the next giant breakthrough to seamlessly link a biological brain to a mechanical hand.

Here’s what Sundaram laid out to get us to that future.

How Does Touch Work, Anyway?
Let me start with some bad news: reverse engineering the human hand is really hard. It’s jam-packed with over 17,000 sensors tuned to mechanical forces alone, not to mention sensors for temperature and pain. These force “receptors” rely on physical distortions—bending, stretching, curling—to signal to the brain.

The good news? We now have a far clearer picture of how biological touch works. Imagine a coin pressed into your palm. The sensors embedded in the skin, called mechanoreceptors, capture that pressure, and “translate” it into electrical signals. These signals pulse through the nerves on your hand to the spine, and eventually make their way to the brain, where they gets interpreted as “touch.”

At least, that’s the simple version, but one too vague and not particularly useful for recapitulating touch. To get there, we need to zoom in.

The cells on your hand that collect touch signals, called tactile “first order” neurons (enter Star Wars joke) are like upside-down trees. Intricate branches extend from their bodies, buried deep in the skin, to a vast area of the hand. Each neuron has its own little domain called “receptor fields,” although some overlap. Like governors, these neurons manage a semi-dedicated region, so that any signal they transfer to the higher-ups—spinal cord and brain—is actually integrated from multiple sensors across a large distance.

It gets more intricate. The skin itself is a living entity that can regulate its own mechanical senses through hydration. Sweat, for example, softens the skin, which changes how it interacts with surrounding objects. Ever tried putting a glove onto a sweaty hand? It’s far more of a struggle than a dry one, and feels different.

In a way, the hand’s tactile neurons play a game of Morse Code. Through different frequencies of electrical beeps, they’re able to transfer information about an object’s size, texture, weight, and other properties, while also asking the brain for feedback to better control the object.

Biology to Machine
Reworking all of our hands’ greatest features into machines is absolutely daunting. But robots have a leg up—they’re not restricted to biological hardware. Earlier this year, for example, a team from Columbia engineered a “feeling” robotic finger using overlapping light emitters and sensors in a way loosely similar to receptor fields. Distortions in light were then analyzed with deep learning to translate into contact location and force.

Although a radical departure from our own electrical-based system, the Columbia team’s attempt was clearly based on human biology. They’re not alone. “Substantial progress is being made in the creation of soft, stretchable electronic skins,” said Sundaram, many of which can sense forces or pressure, although they’re currently still limited.

What’s promising, however, is the “exciting progress in using visual data,” said Sundaram. Computer vision has gained enormously from ubiquitous cameras and large datasets, making it possible to train powerful but data-hungry algorithms such as deep convolutional neural networks (CNNs).

By piggybacking on their success, we can essentially add “eyes” to robotic hands, a superpower us humans can’t imagine. Even better, CNNs and other classes of algorithms can be readily adopted for processing tactile data. Together, a robotic hand could use its eyes to scan an object, plan its movements for grasp, and use touch for feedback to adjust its grip. Maybe we’ll finally have a robot that easily rescues the phone sadly dropped into a composting toilet. Or something much grander to benefit humanity.

That said, relying too heavily on vision could also be a downfall. Take a robot that scans a wide area of rubble for signs of life during a disaster response. If touch relies on sight, then it would have to keep a continuous line-of-sight in a complex and dynamic setting—something computer vision doesn’t do well in, at least for now.

A Neuromorphic Way Forward
Too Debbie Downer? I got your back! It’s hard to overstate the challenges, but what’s clear is that emerging machine learning tools can tackle data processing challenges. For vision, it’s distilling complex images into “actionable control policies,” said Sundaram. For touch, it’s easy to imagine the same. Couple the two together, and that’s a robotic super-hand in the making.

Going forward, argues Sundaram, we need to closely adhere to how the hand and brain process touch. Hijacking our biological “touch machinery” has already proved useful. In 2019, one team used a nerve-machine interface for amputees to control a robotic arm—the DEKA LUKE arm—and sense what the limb and attached hand were feeling. Pressure on the LUKE arm and hand activated an implanted neural interface, which zapped remaining nerves in a way that the brain processes as touch. When the AI analyzed pressure data similar to biological tactile neurons, the person was able to better identify different objects with their eyes closed.

“Neuromorphic tactile hardware (and software) advances will strongly influence the future of bionic prostheses—a compelling application of robotic hands,” said Sundaram, adding that the next step is to increase the density of sensors.

Two additional themes made the list of progressing towards a cyborg future. One is longevity, in that sensors on a robot need to be able to reliably produce large quantities of high-quality data—something that’s seemingly mundane, but is a practical limitation.

The other is going all-in-one. Rather than just a pressure sensor, we need something that captures the myriad of touch sensations. From feather-light to a heavy punch, from vibrations to temperatures, a tree-like architecture similar to our hands would help organize, integrate, and otherwise process data collected from those sensors.

Just a decade ago, mind-controlled robotics were considered a blue sky, stretch-goal neurotechnological fantasy. We now have a chance to “close the loop,” from thought to movement to touch and back to thought, and make some badass robots along the way.

Image Credit: PublicDomainPictures from Pixabay Continue reading →

Posted in Human Robots