Tag Archives: PLACE

#435707 AI Agents Startle Researchers With ...

After 25 million games, the AI agents playing hide-and-seek with each other had mastered four basic game strategies. The researchers expected that part.

After a total of 380 million games, the AI players developed strategies that the researchers didn’t know were possible in the game environment—which the researchers had themselves created. That was the part that surprised the team at OpenAI, a research company based in San Francisco.

The AI players learned everything via a machine learning technique known as reinforcement learning. In this learning method, AI agents start out by taking random actions. Sometimes those random actions produce desired results, which earn them rewards. Via trial-and-error on a massive scale, they can learn sophisticated strategies.

In the context of games, this process can be abetted by having the AI play against another version of itself, ensuring that the opponents will be evenly matched. It also locks the AI into a process of one-upmanship, where any new strategy that emerges forces the opponent to search for a countermeasure. Over time, this “self-play” amounted to what the researchers call an “auto-curriculum.”

According to OpenAI researcher Igor Mordatch, this experiment shows that self-play “is enough for the agents to learn surprising behaviors on their own—it’s like children playing with each other.”

Reinforcement is a hot field of AI research right now. OpenAI’s researchers used the technique when they trained a team of bots to play the video game Dota 2, which squashed a world-champion human team last April. The Alphabet subsidiary DeepMind has used it to triumph in the ancient board game Go and the video game StarCraft.

Aniruddha Kembhavi, a researcher at the Allen Institute for Artificial Intelligence (AI2) in Seattle, says games such as hide-and-seek offer a good way for AI agents to learn “foundational skills.” He worked on a team that taught their AllenAI to play Pictionary with humans, viewing the gameplay as a way for the AI to work on common sense reasoning and communication. “We are, however, quite far away from being able to translate these preliminary findings in highly simplified environments into the real world,” says Kembhavi.

Illustration: OpenAI

AI agents construct a fort during a hide-and-seek game developed by OpenAI.

In OpenAI’s game of hide-and-seek, both the hiders and the seekers received a reward only if they won the game, leaving the AI players to develop their own strategies. Within a simple 3D environment containing walls, blocks, and ramps, the players first learned to run around and chase each other (strategy 1). The hiders next learned to move the blocks around to build forts (2), and then the seekers learned to move the ramps (3), enabling them to jump inside the forts. Then the hiders learned to move all the ramps into their forts before the seekers could use them (4).

The two strategies that surprised the researchers came next. First the seekers learned that they could jump onto a box and “surf” it over to a fort (5), allowing them to jump in—a maneuver that the researchers hadn’t realized was physically possible in the game environment. So as a final countermeasure, the hiders learned to lock all the boxes into place (6) so they weren’t available for use as surfboards.

Illustration: OpenAI

An AI agent uses a nearby box to surf its way into a competitor’s fort.

In this circumstance, having AI agents behave in an unexpected way wasn’t a problem: They found different paths to their rewards, but didn’t cause any trouble. However, you can imagine situations in which the outcome would be rather serious. Robots acting in the real world could do real damage. And then there’s Nick Bostrom’s famous example of a paper clip factory run by an AI, whose goal is to make as many paper clips as possible. As Bostrom told IEEE Spectrum back in 2014, the AI might realize that “human bodies consist of atoms, and those atoms could be used to make some very nice paper clips.”

Bowen Baker, another member of the OpenAI research team, notes that it’s hard to predict all the ways an AI agent will act inside an environment—even a simple one. “Building these environments is hard,” he says. “The agents will come up with these unexpected behaviors, which will be a safety problem down the road when you put them in more complex environments.”

AI researcher Katja Hofmann at Microsoft Research Cambridge, in England, has seen a lot of gameplay by AI agents: She started a competition that uses Minecraft as the playing field. She says the emergent behavior seen in this game, and in prior experiments by other researchers, shows that games can be a useful for studies of safe and responsible AI.

“I find demonstrations like this, in games and game-like settings, a great way to explore the capabilities and limitations of existing approaches in a safe environment,” says Hofmann. “Results like these will help us develop a better understanding on how to validate and debug reinforcement learning systems–a crucial step on the path towards real-world applications.”

Baker says there’s also a hopeful takeaway from the surprises in the hide-and-seek experiment. “If you put these agents into a rich enough environment they will find strategies that we never knew were possible,” he says. “Maybe they can solve problems that we can’t imagine solutions to.” Continue reading

Posted in Human Robots

#435669 Watch World Champion Soccer Robots Take ...

RoboCup 2019 took place earlier this month down in Sydney, Australia. While there are many different events including RoboCup@Home, RoboCup Rescue, and a bunch of different soccer leagues, one of the most compelling events is middle-size league (MSL), where mobile robots each about the size of a fire hydrant play soccer using a regular size FIFA soccer ball. The robots are fully autonomous, making their own decisions in real time about when to dribble, pass, and shoot.

The long-term goal of RoboCup is this:

By the middle of the 21st century, a team of fully autonomous humanoid robot soccer players shall win a soccer game, complying with the official rules of FIFA, against the winner of the most recent World Cup.

While the robots are certainly not there yet, they're definitely getting closer.

Even if you’re not a particular fan of soccer, it’s impressive to watch the robots coordinate with each other, setting up multiple passes and changing tactics on the fly in response to the movements of the other team. And the ability of these robots to shoot accurately is world-class (like, human world-class), as they’re seemingly able to put the ball in whatever corner of the goal they choose with split-second timing.

The final match was between Tech United from Eindhoven University of Technology in the Netherlands (whose robots are called TURTLE), and Team Water from Beijing Information Science & Technology University. Without spoiling it, I can tell you that the game was tied within just the last few seconds, meaning that it had to go to overtime. You can watch the entire match on YouTube, or a 5-minute commentated highlight video here:

It’s become a bit of a tradition to have the winning MSL robots play a team of what looks to be inexperienced adult humans wearing long pants and dress shoes.

The fact that the robots managed to score even once is pretty awesome, and it also looks like the robots are playing very conservatively (more so than the humans) so as not to accidentally injure any of us fragile meatbags with our spindly little legs. I get that RoboCup wants its first team of robots that can beat a human World Cup winning team to be humanoids, but at the moment, the MSL robots are where all the skill is.

To get calibrated on the state of the art for humanoid soccer robots, here’s the adult size final, Team Nimbro from the University of Bonn in Germany versus Team Sweaty from Offenburg University in Germany:

Yup, still a lot of falling over.

There’s lots more RoboCup on YouTube: Some channels to find more matches include the official RoboCup 2019 channel, and Tech United Eindhoven’s channel, which has both live English commentary and some highlight videos.

[ RoboCup 2019 ] Continue reading

Posted in Human Robots

#435660 Toyota Research Developing New ...

With the Olympics taking place next year in Japan, Toyota is (among other things) stepping up its robotics game to help provide “mobility for all.” We know that Toyota’s HSR will be doing work there, along with a few other mobile systems, but the Toyota Research Institute (TRI) has just announced a new telepresence robot called the T-TR1, featuring an absolutely massive screen designed to give you a near-lifesize virtual presence.

T-TR1 is a virtual mobility/tele-presence robot developed by Toyota Research Institute in the United States. It is equipped with a camera atop a large, near-lifesize display.
By projecting an image of a user from a remote location, the robot will help that person feel more physically present at the robot’s location.
With T-TR1, Toyota will give people that are physically unable to attend the events such as the Games a chance to virtually attend, with an on-screen presence capable of conversation between the two locations.

TRI isn’t ready to share much more detail on this system yet (we asked, of course), but we can infer some things from the video and the rest of the info that’s out there. For example, that ball on top is a 360-degree camera (that looks a lot like an Insta360 Pro), giving the remote user just as good of an awareness of their surroundings as they would if they were there in person. There are multiple 3D-sensing systems, including at least two depth cameras plus a lidar at the base. It’s not at all clear whether the robot is autonomous or semi-autonomous (using the sensors for automated obstacle avoidance, say), and since the woman on the other end of the robot does not seem to be controlling it at all for the demo, it’s hard to make an educated guess about the level of autonomy, or even how it’s supposed to be controlled.

We really like that enormous screen—despite the fact that telepresence now requires pants. It adds to the embodiment that makes independent telepresence robots useful.

We really like that enormous screen—despite the fact that telepresence now requires pants. It adds to the embodiment that makes independent telepresence robots useful. It’s also nice that the robot can move fast enough to keep up a person walking briskly. Hopefully, it’s safe for it to move at that speed in an environment more realistic than a carpeted, half-empty conference room, although it’ll probably have to leverage all of those sensors to do so. The other challenge for the T-TR1 will be bandwidth—even assuming that all of the sensor data processing and stuff is done on-robot, 360 cameras are huge bandwidth hogs, plus there’s the primary (presumably high quality) feed from the main camera, and then the video of the user coming the other way. It’s a lot of data in a very latency-sensitive application, and it’ll presumably be operating in places where connectivity is going to be a challenge due to crowds. This has always been a problem for telepresence robots—no matter how amazing your robot is, the experience will often for better or worse be defined by Internet connections that you may have no control over.

We should emphasize that Toyota has only released the bare minimum of information about the T-TR1, although we’re told that we can expect more as the 2020 Olympics approach: opening ceremonies are one year from today.

[ TRI ] Continue reading

Posted in Human Robots

#435646 Video Friday: Kiki Is a New Social Robot ...

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!):

DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

The DARPA Subterranean Challenge tunnel circuit takes place in just a few weeks, and we’ll be there!

[ DARPA SubT ]

Time lapse video of robotic arm on NASA’s Mars 2020 rover handily maneuvers 88-pounds (40 kilograms) worth of sensor-laden turret as it moves from a deployed to stowed configuration.

If you haven’t read our interview with Matt Robinson, now would be a great time, since he’s one of the folks at JPL who designed this arm.

[ Mars 2020 ]

Kiki is a small, white, stationary social robot with an evolving personality who promises to be your friend and costs $800 and is currently on Kickstarter.

The Kickstarter page is filled with the same type of overpromising that we’ve seen with other (now very dead) social robots: Kiki is “conscious,” “understands your feelings,” and “loves you back.” Oof. That said, we’re happy to see more startups trying to succeed in this space, which is certainly one of the toughest in consumer electronics, and hopefully they’ve been learning from the recent string of failures. And we have to say Kiki is a cute robot. Its overall design, especially the body mechanics and expressive face, look neat. And kudos to the team—the company was founded by two ex-Googlers, Mita Yun and Jitu Das—for including the “unedited prototype videos,” which help counterbalance the hype.

Another thing that Kiki has going for it is that everything runs on the robot itself. This simplifies privacy and means that the robot won’t partially die on you if the company behind it goes under, but also limits how clever the robot will be able to be. The Kickstarter campaign is already over a third funded, so…We’ll see.

[ Kickstarter ]

When your UAV isn’t enough UAV, so you put a UAV on your UAV.

[ CanberraUAV ]

ABB’s YuMi is testing ATMs because a human trying to do this task would go broke almost immediately.

[ ABB ]

DJI has a fancy new FPV system that features easy setup, digital HD streaming at up to 120 FPS, and <30ms latency.

If it looks expensive, that’s because it costs $930 with the remote included.

[ DJI ]

Honeybee Robotics has recently developed a regolith excavation and rock cleaning system for NASA JPL’s PUFFER rovers. This system, called POCCET (PUFFER-Oriented Compact Cleaning and Excavation Tool), uses compressed gas to perform all excavation and cleaning tasks. Weighing less than 300 grams with potential for further mass reduction, POCCET can be used not just on the Moon, but on other Solar System bodies such as asteroids, comets, and even Mars.

[ Honeybee Robotics ]

DJI’s 2019 RoboMaster tournament, which takes place this month in Shenzen, looks like it’ll be fun to watch, with a plenty of action and rules that are easy to understand.

[ RoboMaster ]

Robots and baked goods are an automatic Video Friday inclusion.

Wow I want a cupcake right now.

[ Soft Robotics ]

The ICRA 2019 Best Paper Award went to Michelle A. Lee at Stanford, for “Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks.”

The ICRA video is here, and you can find the paper at the link below.

[ Paper ] via [ RoboHub ]

Cobalt Robotics put out a bunch of marketing-y videos this week, but this one reasonably interesting, even if you’re familiar with what they’re doing over there.

[ Cobalt Robotics ]

RightHand Robotics launched RightPick2 with a gala event which looked like fun as long as you were really, really in to robots.

[ RightHand Robotics ]

Thanks Jeff!

This video presents a framework for whole-body control applied to the assistive robotic system EDAN. We show how the proposed method can be used for a task like open, pass through and close a door. Also, we show the efficiency of the whole-body coordination with controlling the end-effector with respect to a fixed reference. Additionally, showing how easy the system can be manually manoeuvred by direct interaction with the end-effector, without the need for an extra input device.

[ DLR ]

You’ll probably need to turn on auto-translated subtitles for most of this, but it’s worth it for the adorable little single-seat robotic car designed to help people get around airports.

[ ZMP ]

In this week’s episode of Robots in Depth, Per speaks with Gonzalo Rey from Moog about their fancy 3D printed integrated hydraulic actuators.

Gonzalo talks about how Moog got started with hydraulic control,taking part in the space program and early robotics development. He shares how Moog’s technology is used in fly-by-wire systems in aircraft and in flow control in deep space probes. They have even reached Mars.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435640 Video Friday: This Wearable Robotic Tail ...

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!):

DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
CLAWAR 2019 – August 26-28, 2019 – Kuala Lumpur, Malaysia
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.

Lakshmi Nair from Georgia Tech describes some fascinating research towards robots that can create their own tools, as presented at ICRA this year:

Using a novel capability to reason about shape, function, and attachment of unrelated parts, researchers have for the first time successfully trained an intelligent agent to create basic tools by combining objects.

The breakthrough comes from Georgia Tech’s Robot Autonomy and Interactive Learning (RAIL) research lab and is a significant step toward enabling intelligent agents to devise more advanced tools that could prove useful in hazardous – and potentially life-threatening – environments.

[ Lakshmi Nair ]

Victor Barasuol, from the Dynamic Legged Systems Lab at IIT, wrote in to share some new research on their HyQ quadruped that enables sensorless shin collision detection. This helps the robot navigate unstructured environments, and also mitigates all those painful shin strikes, because ouch.

This will be presented later this month at the International Conference on Climbing and Walking Robots (CLAWAR) in Kuala Lumpur, Malaysia.

[ IIT ]

Thanks Victor!

You used to have a tail, you know—as an embryo, about a month in to your development. All mammals used to have tails, and now we just have useless tailbones, which don’t help us with balancing even a little bit. BRING BACK THE TAIL!

The tail, created by Junichi Nabeshima, Kouta Minamizawa, and MHD Yamen Saraiji from Keio University’s Graduate School of Media Design, was presented at SIGGRAPH 2019 Emerging Technologies.

[ Paper ] via [ Gizmodo ]

The noises in this video are fantastic.

[ ESA ]

Apparently the industrial revolution wasn’t a thorough enough beatdown of human knitting, because the robots are at it again.

[ MIT CSAIL ]

Skydio’s drones just keep getting more and more impressive. Now if only they’d make one that I can afford…

[ Skydio ]

The only thing more fun than watching robots is watching people react to robots.

[ SEER ]

There aren’t any robots in this video, but it’s robotics-related research, and very soothing to watch.

[ Stanford ]

#autonomousicecreamtricycle

In case it wasn’t clear, which it wasn’t, this is a Roboy project. And if you didn’t understand that first video, you definitely won’t understand this second one:

Whatever that t-shirt is at the end (Roboy in sunglasses puking rainbows…?) I need one.

[ Roboy ]

By adding electronics and computation technology to a simple cane that has been around since ancient times, a team of researchers at Columbia Engineering have transformed it into a 21st century robotic device that can provide light-touch assistance in walking to the aged and others with impaired mobility.

The light-touch robotic cane, called CANINE, acts as a cane-like mobile assistant. The device improves the individual’s proprioception, or self-awareness in space, during walking, which in turn improves stability and balance.

[ ROAR Lab ]

During the second field experiment for DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) program, which took place at Fort Benning, Georgia, teams of autonomous air and ground robots tested tactics on a mission to isolate an urban objective. Similar to the way a firefighting crew establishes a boundary around a burning building, they first identified locations of interest and then created a perimeter around the focal point.

[ DARPA ]

I think there’s a bit of new footage here of Ghost Robotics’ Vision 60 quadruped walking around without sensors on unstructured terrain.

[ Ghost Robotics ]

If you’re as tired of passenger drone hype as I am, there’s absolutely no need to watch this video of NEC’s latest hover test.

[ AP ]

As researchers teach robots to perform more and more complex tasks, the need for realistic simulation environments is growing. Existing techniques for closing the reality gap by approximating real-world physics often require extensive real world data and/or thousands of simulation samples. This paper presents TuneNet, a new machine learning-based method to directly tune the parameters of one model to match another using an iterative residual tuning technique. TuneNet estimates the parameter difference between two models using a single observation from the target and minimal simulation, allowing rapid, accurate and sample-efficient parameter estimation.

The system can be trained via supervised learning over an auto-generated simulated dataset. We show that TuneNet can perform system identification, even when the true parameter values lie well outside the distribution seen during training, and demonstrate that simulators tuned with TuneNet outperform existing techniques for predicting rigid body motion. Finally, we show that our method can estimate real-world parameter values, allowing a robot to perform sim-to-real task transfer on a dynamic manipulation task unseen during training. We are also making a baseline implementation of our code available online.

[ Paper ]

Here’s an update on what GITAI has been up to with their telepresence astronaut-replacement robot.

[ GITAI ]

Curiosity captured this 360-degree panorama of a location on Mars called “Teal Ridge” on June 18, 2019. This location is part of a larger region the rover has been exploring called the “clay-bearing unit” on the side of Mount Sharp, which is inside Gale Crater. The scene is presented with a color adjustment that approximates white balancing to resemble how the rocks and sand would appear under daytime lighting conditions on Earth.

[ MSL ]

Some updates (in English) on ROS from ROSCon France. The first is a keynote from Brian Gerkey:

And this second video is from Omri Ben-Bassat, about how to keep your Anki Vector alive using ROS:

All of the ROSCon FR talks are available on Vimeo.

[ ROSCon FR ] Continue reading

Posted in Human Robots