Tag Archives: human-like

#437386 Scary A.I. more intelligent than you

GPT-3 (Generative Pre-trained Transformer 3), is an artificial intelligence language generator that uses deep learning to produce human-like output. The high quality of its text is very difficult to distinguish from a human’s. Many scientists, researchers and engineers (including Stephen … Continue reading

Posted in Human Robots

#439066 Video Friday: Festo’s BionicSwift

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!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USA
WeRobot 2021 – September 23-25, 2021 – Coral Gables, FL, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

Festo's Bionic Learning Network for 2021 presents a flock of BionicSwifts.

To execute the flight maneuvers as true to life as possible, the wings are modeled on the plumage of birds. The individual lamellae are made of an ultralight, flexible but very robust foam and lie on top of each other like shingles. Connected to a carbon quill, they are attached to the actual hand and arm wings as in the natural model.

During the wing upstroke, the individual lamellae fan out so that air can flow through the wing. This means that the birds need less force to pull the wing up. During the downstroke, the lamellae close up so that the birds can generate more power to fly. Due to this close-to-nature replica of the wings, the BionicSwifts have a better flight profile than previous wing-beating drives.

[ Festo ]

While we've seen a wide variety of COVID-motivated disinfecting robots, they're usually using either ultraviolet light or a chemical fog. This isn't the way that humans clean—we wipe stuff down, which gets rid of surface dirt and disinfects at the same time. Fraunhofer has been working on a mobile manipulator that can clean in the same ways that we do.

It's quite the technical challenge, but it has the potential to be both more efficient and more effective.

[ Fraunhofer ]

In recent years, robots have gained artificial vision, touch, and even smell. “Researchers have been giving robots human-like perception,” says MIT Associate Professor Fadel Adib. In a new paper, Adib’s team is pushing the technology a step further. “We’re trying to give robots superhuman perception,” he says. The researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects. The robot, called RF-Grasp, combines this powerful sensing with more traditional computer vision to locate and grasp items that might otherwise be blocked from view.

[ MIT ]

Ingenuity is now scheduled to fly on April 11.

[ JPL ]

The legendary Zenta is back after a two year YouTube hiatus with “a kind of freaky furry hexapod bunny creature.”

[ Zenta ]

It is with great pride and excitement that the South Australia Police announce a new expansion to their kennel by introducing three new Police Dog (PD) recruits. These dogs have been purposely targeted to bring a whole new range of dog operational capabilities known as the ‘small area urban search and guided evacuation’ dogs. Police have been working closely with specialist vets and dog trainers to ascertain if the lightweight dogs could be transported safely by drones and released into hard-to-access areas where at the moment the larger PDs just simply cannot get in due to their size.

[ SA Police ]

SoftBank may not have Spot cheerleading robots for their baseball team anymore, but they've more than made up for it with a full century of Peppers. And one dude doing the robot.

[ SoftBank ]

MAB Robotics is a Polish company developing walking robots for inspection, and here's a prototype they've been working on.

[ MAB Robotics ]

Thanks Jakub!

DoraNose: Smell your way to a better tomorrow.

[ Dorabot ]

Our robots need to learn how to cope with their new neighbors, and we have just the solution for this, the egg detector! Using cutting-edge AI, it provides incredible precision in detecting a vast variety of eggs. We have deployed this new feature on Boston Dynamics Spot, one of our fleet's robots. It can now detect eggs with its cameras and avoid them on his autonomous missions.

[ Energy Robotics ]

When dropping a squishy robot from an airplane 1,000 feet up, make sure that you land as close to people's cars as you can.

Now do it from orbit!

[ Squishy Robotics ]

An autonomous robot that is able to physically guide humans through narrow and cluttered spaces could be a big boon to the visually-impaired. Most prior robotic guiding systems are based on wheeled platforms with large bases with actuated rigid guiding canes. The large bases and the actuated arms limit these prior approaches from operating in narrow and cluttered environments. We propose a method that introduces a quadrupedal robot with a leash to enable the robot-guiding-human system to change its intrinsic dimension (by letting the leash go slack) in order to fit into narrow spaces.

[ Hybrid Robotics ]

How to prove that your drone is waterproof.

[ UNL ]

Well this ought to be pretty good once it gets out of simulation.

[ Hybrid Robotics ]

MIDAS is Aurora’s AI-enabled, multi-rotor sUAV outfitted with optical sensors and a customized payload that can defeat multiple small UAVs per flight with low-collateral effects.

[ Aurora ]

The robots​ of the DFKI have the advantage of being able to reach extreme environments: they can be used for decontamination purposes in high-risk areas or inspect and maintain underwater​ structures, for which they are tested in the North Sea near Heligoland​.

[ DFKI ]

After years of trying, 60 Minutes cameras finally get a peek inside the workshop at Boston Dynamics, where robots move in ways once only thought possible in movies. Anderson Cooper reports.

[ 60 Minutes ]

In 2007, Noel Sharky stated that “we are sleepwalking into a brave new world where robots decide who, where and when to kill.” Since then thousands of AI and robotics researchers have joined his calls to regulate “killer robots.” But sometime this year, Turkey will deploy fully autonomous home-built kamikaze drones on its border with Syria. What are the ethical choices we need to consider? Will we end up in an episode of Black Mirror? Or is the UN listening to calls and starting the process of regulating this space? Prof. Toby Walsh will discuss this important issue, consider where we are at and where we need to go.

[ ICRA 2020 ]

In the second session of HAI's spring conference, artists and technologists discussed how technology can enhance creativity, reimagine meaning, and support racial and social justice. The conference, called “Intelligence Augmentation: AI Empowering People to Solve Global Challenges,” took place on 25 March 2021.

[ Stanford HAI ]

This spring 2021 GRASP SFI comes from Monroe Kennedy III at Stanford University, on “Considerations for Human-Robot Collaboration.”

The field of robotics has evolved over the past few decades. We’ve seen robots progress from the automation of repetitive tasks in manufacturing to the autonomy of mobilizing in unstructured environments to the cooperation of swarm robots that are centralized or decentralized. These abilities have required advances in robotic hardware, modeling, and artificial intelligence. The next frontier is robots collaborating in complex tasks with human teammates, in environments traditionally configured for humans. While solutions to this challenge must utilize all the advances of robotics, the human element adds a unique aspect that must be addressed. Collaborating with a human teammate means that the robot must have a contextual understanding of the task as well as all participant’s roles. We will discuss what constitutes an effective teammate and how we can capture this behavior in a robotic collaborator.

[ UPenn ] Continue reading

Posted in Human Robots

#439053 Bipedal Robots Are Learning To Move With ...

Most humans are bipeds, but even the best of us are really only bipeds until things get tricky. While our legs may be our primary mobility system, there are lots of situations in which we leverage our arms as well, either passively to keep balance or actively when we put out a hand to steady ourselves on a nearby object. And despite how unstable bipedal robots tend to be, using anything besides legs for mobility has been a challenge in both software and hardware, a significant limitation in highly unstructured environments.

Roboticists from TUM in Germany (with support from the German Research Foundation) have recently given their humanoid robot LOLA some major upgrades to make this kind of multi-contact locomotion possible. While it’s still in the early stages, it’s already some of the most human-like bipedal locomotion we’ve seen.

It’s certainly possible for bipedal robots to walk over challenging terrain without using limbs for support, but I’m sure you can think of lots of times where using your arms to assist with your own bipedal mobility was a requirement. It’s not a requirement because your leg strength or coordination or sense of balance is bad, necessarily. It’s just that sometimes, you might find yourself walking across something that’s highly unstable or in a situation where the consequences of a stumble are exceptionally high. And it may not even matter how much sensing you do beforehand, and how careful you are with your footstep planning: there are limits to how much you can know about your environment beforehand, and that can result in having a really bad time of it. This is why using multi-contact locomotion, whether it’s planned in advance or not, is a useful skill for humans, and should be for robots, too.

As the video notes (and props for being explicit up front about it), this isn’t yet fully autonomous behavior, with foot positions and arm contact points set by hand in advance. But it’s not much of a stretch to see how everything could be done autonomously, since one of the really hard parts (using multiple contact points to dynamically balance a moving robot) is being done onboard and in real time.

Getting LOLA to be able to do this required a major overhaul in hardware as well as software. And Philipp Seiwald, who works with LOLA at TUM, was able to tell us more about it.

IEEE Spectrum: Can you summarize the changes to LOLA’s hardware that are required for multi-contact locomotion?

Philipp Seiwald: The original version of LOLA has been designed for fast biped walking. Although it had two arms, they were not meant to get into contact with the environment but rather to compensate for the dynamic effects of the feet during fast walking. Also, the torso had a relatively simple design that was fine for its original purpose; however, it was not conceived to withstand the high loads coming from the hands during multi-contact maneuvers. Thus, we redesigned the complete upper body of LOLA from scratch. Starting from the pelvis, the strength and stiffness of the torso have been increased. We used the finite element method to optimize critical parts to obtain maximum strength at minimum weight. Moreover, we added additional degrees of freedom to the arms to increase the hands' reachable workspace. The kinematic topology of the arms, i.e., the arrangement of joints and link lengths, has been obtained from an optimization that takes typical multi-contact scenarios into account.

Why is this an important problem for bipedal humanoid robots?

Maintaining balance during locomotion can be considered the primary goal of legged robots. Naturally, this task is more challenging for bipeds when compared to robots with four or even more legs. Although current high-end prototypes show impressive progress, humanoid robots still do not have the robustness and versatility they need for most real-world applications. With our research, we try to contribute to this field and help to push the limits further. Recently, we showed our latest work on walking over uneven terrain without multi-contact support. Although the robustness is already high, there still exist scenarios, such as walking on loose objects, where the robot's stabilization fails when using only foot contacts. The use of additional hand-environment support during this (comparatively) fast walking allows a further significant increase in robustness, i.e., the robot's capability to compensate disturbances, modeling errors, or inaccurate sensor input. Besides stabilization on uneven terrain, multi-contact locomotion also enables more complex motions, e.g., stepping over a tall obstacle or toe-only contacts, as shown in our latest multi-contact video.

How can LOLA decide whether a surface is suitable for multi-contact locomotion?

LOLA’s visual perception system is currently developed by our project partners from the Chair for Computer Aided Medical Procedures & Augmented Reality at the TUM. This system relies on a novel semantic Simultaneous Localization and Mapping (SLAM) pipeline that can robustly extract the scene's semantic components (like floor, walls, and objects therein) by merging multiple observations from different viewpoints and by inferring therefrom the underlying scene graph. This provides a reliable estimate of which scene parts can be used to support the locomotion, based on the assumption that certain structural elements such as walls are fixed, while chairs, for example, are not.

Also, the team plans to develop a specific dataset with annotations further describing the attributes of the object (such as roughness of the surface or its softness) and that will be used to master multi-contact locomotion in even more complex scenes. As of today, the vision and navigation system is not finished yet; thus, in our latest video, we used pre-defined footholds and contact points for the hands. However, within our collaboration, we are working towards a fully integrated and autonomous system.

Is LOLA capable of both proactive and reactive multi-contact locomotion?

The software framework of LOLA has a hierarchical structure. On the highest level, the vision system generates an environment model and estimates the 6D-pose of the robot in the scene. The walking pattern generator then uses this information to plan a dynamically feasible future motion that will lead LOLA to a target position defined by the user. On a lower level, the stabilization module modifies this plan to compensate for model errors or any kind of disturbance and keep overall balance. So our approach currently focuses on proactive multi-contact locomotion. However, we also plan to work on a more reactive behavior such that additional hand support can also be triggered by an unexpected disturbance instead of being planned in advance.

What are some examples of unique capabilities that you are working towards with LOLA?

One of the main goals for the research with LOLA remains fast, autonomous, and robust locomotion on complex, uneven terrain. We aim to reach a walking speed similar to humans. Currently, LOLA can do multi-contact locomotion and cross uneven terrain at a speed of 1.8 km/h, which is comparably fast for a biped robot but still slow for a human. On flat ground, LOLA's high-end hardware allows it to walk at a relatively high maximum speed of 3.38 km/h.

Fully autonomous multi-contact locomotion for a life-sized humanoid robot is a tough task. As algorithms get more complex, computation time increases, which often results in offline motion planning methods. For LOLA, we restrict ourselves to gaited multi-contact locomotion, which means that we try to preserve the core characteristics of bipedal gait and use the arms only for assistance. This allows us to use simplified models of the robot which lead to very efficient algorithms running in real-time and fully onboard.

A long-term scientific goal with LOLA is to understand essential components and control policies of human walking. LOLA's leg kinematics is relatively similar to the human body. Together with scientists from kinesiology, we try to identify similarities and differences between observed human walking and LOLA’s “engineered” walking gait. We hope this research leads, on the one hand, to new ideas for the control of bipeds, and on the other hand, shows via experiments on bipeds if biomechanical models for the human gait are correctly understood. For a comparison of control policies on uneven terrain, LOLA must be able to walk at comparable speeds, which also motivates our research on fast and robust walking.

While it makes sense why the researchers are using LOLA’s arms primarily to assist with a conventional biped gait, looking ahead a bit it’s interesting to think about how robots that we typically consider to be bipeds could potentially leverage their limbs for mobility in decidedly non-human ways.

We’re used to legged robots being one particular morphology, I guess because associating them with either humans or dogs or whatever is just a comfortable way to do it, but there’s no particular reason why a robot with four limbs has to choose between being a quadruped and being a biped with arms, or some hybrid between the two, depending on what its task is. The research being done with LOLA could be a step in that direction, and maybe a hand on the wall in that direction, too. Continue reading

Posted in Human Robots

#437423 Robonaut2 joins ISS (2011)

Space Shuttle Discovery carried the humanoid robot Robonaut2 (also known as R2) to the International Space Station (ISS) as part of STS-133. Robonaut2 originally consisted only of a torso, made out of nickel-plated carbon fiber and aluminum. A pair of … Continue reading

Posted in Human Robots

#437957 Meet Assembloids, Mini Human Brains With ...

It’s not often that a twitching, snowman-shaped blob of 3D human tissue makes someone’s day.

But when Dr. Sergiu Pasca at Stanford University witnessed the tiny movement, he knew his lab had achieved something special. You see, the blob was evolved from three lab-grown chunks of human tissue: a mini-brain, mini-spinal cord, and mini-muscle. Each individual component, churned to eerie humanoid perfection inside bubbling incubators, is already a work of scientific genius. But Pasca took the extra step, marinating the three components together inside a soup of nutrients.

The result was a bizarre, Lego-like human tissue that replicates the basic circuits behind how we decide to move. Without external prompting, when churned together like ice cream, the three ingredients physically linked up into a fully functional circuit. The 3D mini-brain, through the information highway formed by the artificial spinal cord, was able to make the lab-grown muscle twitch on demand.

In other words, if you think isolated mini-brains—known formally as brain organoids—floating in a jar is creepy, upgrade your nightmares. The next big thing in probing the brain is assembloids—free-floating brain circuits—that now combine brain tissue with an external output.

The end goal isn’t to freak people out. Rather, it’s to recapitulate our nervous system, from input to output, inside the controlled environment of a Petri dish. An autonomous, living brain-spinal cord-muscle entity is an invaluable model for figuring out how our own brains direct the intricate muscle movements that allow us stay upright, walk, or type on a keyboard.

It’s the nexus toward more dexterous brain-machine interfaces, and a model to understand when brain-muscle connections fail—as in devastating conditions like Lou Gehrig’s disease or Parkinson’s, where people slowly lose muscle control due to the gradual death of neurons that control muscle function. Assembloids are a sort of “mini-me,” a workaround for testing potential treatments on a simple “replica” of a person rather than directly on a human.

From Organoids to Assembloids
The miniature snippet of the human nervous system has been a long time in the making.

It all started in 2014, when Dr. Madeleine Lancaster, then a post-doc at Stanford, grew a shockingly intricate 3D replica of human brain tissue inside a whirling incubator. Revolutionarily different than standard cell cultures, which grind up brain tissue to reconstruct as a flat network of cells, Lancaster’s 3D brain organoids were incredibly sophisticated in their recapitulation of the human brain during development. Subsequent studies further solidified their similarity to the developing brain of a fetus—not just in terms of neuron types, but also their connections and structure.

With the finding that these mini-brains sparked with electrical activity, bioethicists increasingly raised red flags that the blobs of human brain tissue—no larger than the size of a pea at most—could harbor the potential to develop a sense of awareness if further matured and with external input and output.

Despite these concerns, brain organoids became an instant hit. Because they’re made of human tissue—often taken from actual human patients and converted into stem-cell-like states—organoids harbor the same genetic makeup as their donors. This makes it possible to study perplexing conditions such as autism, schizophrenia, or other brain disorders in a dish. What’s more, because they’re grown in the lab, it’s possible to genetically edit the mini-brains to test potential genetic culprits in the search for a cure.

Yet mini-brains had an Achilles’ heel: not all were made the same. Rather, depending on the region of the brain that was reverse engineered, the cells had to be persuaded by different cocktails of chemical soups and maintained in isolation. It was a stark contrast to our own developing brains, where regions are connected through highways of neural networks and work in tandem.

Pasca faced the problem head-on. Betting on the brain’s self-assembling capacity, his team hypothesized that it might be possible to grow different mini-brains, each reflecting a different brain region, and have them fuse together into a synchronized band of neuron circuits to process information. Last year, his idea paid off.

In one mind-blowing study, his team grew two separate portions of the brain into blobs, one representing the cortex, the other a deeper part of the brain known to control reward and movement, called the striatum. Shockingly, when put together, the two blobs of human brain tissue fused into a functional couple, automatically establishing neural highways that resulted in one of the most sophisticated recapitulations of a human brain. Pasca crowned this tissue engineering crème-de-la-crème “assembloids,” a portmanteau between “assemble” and “organoids.”

“We have demonstrated that regionalized brain spheroids can be put together to form fused structures called brain assembloids,” said Pasca at the time.” [They] can then be used to investigate developmental processes that were previously inaccessible.”

And if that’s possible for wiring up a lab-grown brain, why wouldn’t it work for larger neural circuits?

Assembloids, Assemble
The new study is the fruition of that idea.

The team started with human skin cells, scraped off of eight healthy people, and transformed them into a stem-cell-like state, called iPSCs. These cells have long been touted as the breakthrough for personalized medical treatment, before each reflects the genetic makeup of its original host.

Using two separate cocktails, the team then generated mini-brains and mini-spinal cords using these iPSCs. The two components were placed together “in close proximity” for three days inside a lab incubator, gently floating around each other in an intricate dance. To the team’s surprise, under the microscope using tracers that glow in the dark, they saw highways of branches extending from one organoid to the other like arms in a tight embrace. When stimulated with electricity, the links fired up, suggesting that the connections weren’t just for show—they’re capable of transmitting information.

“We made the parts,” said Pasca, “but they knew how to put themselves together.”

Then came the ménage à trois. Once the mini-brain and spinal cord formed their double-decker ice cream scoop, the team overlaid them onto a layer of muscle cells—cultured separately into a human-like muscular structure. The end result was a somewhat bizarre and silly-looking snowman, made of three oddly-shaped spherical balls.

Yet against all odds, the brain-spinal cord assembly reached out to the lab-grown muscle. Using a variety of tools, including measuring muscle contraction, the team found that this utterly Frankenstein-like snowman was able to make the muscle component contract—in a way similar to how our muscles twitch when needed.

“Skeletal muscle doesn’t usually contract on its own,” said Pasca. “Seeing that first twitch in a lab dish immediately after cortical stimulation is something that’s not soon forgotten.”

When tested for longevity, the contraption lasted for up to 10 weeks without any sort of breakdown. Far from a one-shot wonder, the isolated circuit worked even better the longer each component was connected.

Pasca isn’t the first to give mini-brains an output channel. Last year, the queen of brain organoids, Lancaster, chopped up mature mini-brains into slices, which were then linked to muscle tissue through a cultured spinal cord. Assembloids are a step up, showing that it’s possible to automatically sew multiple nerve-linked structures together, such as brain and muscle, sans slicing.

The question is what happens when these assembloids become more sophisticated, edging ever closer to the inherent wiring that powers our movements. Pasca’s study targets outputs, but what about inputs? Can we wire input channels, such as retinal cells, to mini-brains that have a rudimentary visual cortex to process those examples? Learning, after all, depends on examples of our world, which are processed inside computational circuits and delivered as outputs—potentially, muscle contractions.

To be clear, few would argue that today’s mini-brains are capable of any sort of consciousness or awareness. But as mini-brains get increasingly more sophisticated, at what point can we consider them a sort of AI, capable of computation or even something that mimics thought? We don’t yet have an answer—but the debates are on.

Image Credit: christitzeimaging.com / Shutterstock.com Continue reading

Posted in Human Robots