Tag Archives: rescue

#439793 “Kaleido”, Kawasaki’s ...

In this video, Kaleido exhibits its rescue capabilities.

Posted in Human Robots

#439362 An autonomous drone for search and ...

A team of researchers working at Johannes Kepler University has developed an autonomous drone with a new type of technology to improve search-and-rescue efforts. In their paper published in the journal Science Robotics, the group describes their drone modifications. Andreas Birk with Jacobs University Bremen has published a Focus piece in the same journal issue outlining the work by the team in Austria. Continue reading

Posted in Human Robots

#439100 Video Friday: Robotic Eyeball Camera

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
RoboCup 2021 – June 22-28, 2021 – [Online Event]
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.

What if seeing devices looked like us? Eyecam is a prototype exploring the potential future design of sensing devices. Eyecam is a webcam shaped like a human eye that can see, blink, look around and observe us.

And it's open source, so you can build your own!

[ Eyecam ]

Looks like Festo will be turning some of its bionic robots into educational kits, which is a pretty cool idea.

[ Bionics4Education ]

Underwater soft robots are challenging to model and control because of their high degrees of freedom and their intricate coupling with water. In this paper, we present a method that leverages the recent development in differentiable simulation coupled with a differentiable, analytical hydrodynamic model to assist with the modeling and control of an underwater soft robot. We apply this method to Starfish, a customized soft robot design that is easy to fabricate and intuitive to manipulate.

[ MIT CSAIL ]

Rainbow Robotics, the company who made HUBO, has a new collaborative robot arm.

[ Rainbow Robotics ]

Thanks Fan!

We develop an integrated robotic platform for advanced collaborative robots and demonstrates an application of multiple robots collaboratively transporting an object to different positions in a factory environment. The proposed platform integrates a drone, a mobile manipulator robot, and a dual-arm robot to work autonomously, while also collaborating with a human worker. The platform also demonstrates the potential of a novel manufacturing process, which incorporates adaptive and collaborative intelligence to improve the efficiency of mass customization for the factory of the future.

[ Paper ]

Thanks Poramate!

In Sevastopol State University the team of the Laboratory of Underwater Robotics and Control Systems and Research and Production Association “Android Technika” performed tests of an underwater anropomorphic manipulator robot.

[ Sevastopol State ]

Thanks Fan!

Taiwanese company TCI Gene created a COVID test system based on their fully automated and enclosed gene testing machine QVS-96S. The system includes two ABB robots and carries out 1800 tests per day, operating 24/7. Every hour 96 virus samples tests are made with an accuracy of 99.99%.

[ ABB ]

A short video showing how a Halodi Robotics can be used in a commercial guarding application.

[ Halodi ]

During the past five years, under the NASA Early Space Innovations program, we have been developing new design optimization methods for underactuated robot hands, aiming to achieve versatile manipulation in highly constrained environments. We have prototyped hands for NASA’s Astrobee robot, an in-orbit assistive free flyer for the International Space Station.

[ ROAM Lab ]

The new, improved OTTO 1500 is a workhorse AMR designed to move heavy payloads through demanding environments faster than any other AMR on the market, with zero compromise to safety.

[ ROAM Lab ]

Very, very high performance sensing and actuation to pull this off.

[ Ishikawa Group ]

We introduce a conversational social robot designed for long-term in-home use to help with loneliness. We present a novel robot behavior design to have simple self-reflection conversations with people to improve wellness, while still being feasible, deployable, and safe.

[ HCI Lab ]

We are one of the 5 winners of the Start-up Challenge. This video illustrates what we achieved during the Swisscom 5G exploration week. Our proof-of-concept tele-excavation system is composed of a Menzi Muck M545 walking excavator automated & customized by Robotic Systems Lab and IBEX motion platform as the operator station. The operator and remote machine are connected for the first time via a 5G network infrastructure which was brought to our test field by Swisscom.

[ RSL ]

This video shows LOLA balancing on different terrain when being pushed in different directions. The robot is technically blind, not using any camera-based or prior information on the terrain (hard ground is assumed).

[ TUM ]

Autonomous driving when you cannot see the road at all because it's buried in snow is some serious autonomous driving.

[ Norlab ]

A hierarchical and robust framework for learning bipedal locomotion is presented and successfully implemented on the 3D biped robot Digit. The feasibility of the method is demonstrated by successfully transferring the learned policy in simulation to the Digit robot hardware, realizing sustained walking gaits under external force disturbances and challenging terrains not included during the training process.

[ OSU ]

This is a video summary of the Center for Robot-Assisted Search and Rescue's deployments under the direction of emergency response agencies to more than 30 disasters in five countries from 2001 (9/11 World Trade Center) to 2018 (Hurricane Michael). It includes the first use of ground robots for a disaster (WTC, 2001), the first use of small unmanned aerial systems (Hurricane Katrina 2005), and the first use of water surface vehicles (Hurricane Wilma, 2005).

[ CRASAR ]

In March, a team from the Oxford Robotics Institute collected a week of epic off-road driving data, as part of the Sense-Assess-eXplain (SAX) project.

[ Oxford Robotics ]

As a part of the AAAI 2021 Spring Symposium Series, HEBI Robotics was invited to present an Industry Talk on the symposium's topic: Machine Learning for Mobile Robot Navigation in the Wild. Included in this presentation was a short case study on one of our upcoming mobile robots that is being designed to successfully navigate unstructured environments where today's robots struggle.

[ HEBI Robotics ]

Thanks Hardik!

This Lockheed Martin Robotics Seminar is from Chad Jenkins at the University of Michigan, on “Semantic Robot Programming… and Maybe Making the World a Better Place.”

I will present our efforts towards accessible and general methods of robot programming from the demonstrations of human users. Our recent work has focused on Semantic Robot Programming (SRP), a declarative paradigm for robot programming by demonstration that builds on semantic mapping. In contrast to procedural methods for motion imitation in configuration space, SRP is suited to generalize user demonstrations of goal scenes in workspace, such as for manipulation in cluttered environments. SRP extends our efforts to crowdsource robot learning from demonstration at scale through messaging protocols suited to web/cloud robotics. With such scaling of robotics in mind, prospects for cultivating both equal opportunity and technological excellence will be discussed in the context of broadening and strengthening Title IX and Title VI.

[ UMD ] Continue reading

Posted in Human Robots

#439095 DARPA Prepares for the Subterranean ...

The DARPA Subterranean Challenge Final Event is scheduled to take place at the Louisville Mega Cavern in Louisville, Kentucky, from September 21 to 23. We’ve followed SubT teams as they’ve explored their way through abandoned mines, unfinished nuclear reactors, and a variety of caves, and now everything comes together in one final course where the winner of the Systems Track will take home the $2 million first prize.

It’s a fitting reward for teams that have been solving some of the hardest problems in robotics, but winning isn’t going to be easy, and we’ll talk with SubT Program Manager Tim Chung about what we have to look forward to.

Since we haven’t talked about SubT in a little while (what with the unfortunate covid-related cancellation of the Systems Track Cave Circuit), here’s a quick refresher of where we are: the teams have made it through the Tunnel Circuit, the Urban Circuit, and a virtual version of the Cave Circuit, and some of them have been testing in caves of their own. The Final Event will include all of these environments, and the teams of robots will have 60 minutes to autonomously map the course, locating artifacts to score points. Since I’m not sure where on Earth there’s an underground location that combines tunnels and caves with urban structures, DARPA is going to have to get creative, and the location in which they’ve chosen to do that is Louisville, Kentucky.

The Louisville Mega Cavern is a former limestone mine, most of which is under the Louisville Zoo. It’s not all that deep, mostly less than 30 meters under the surface, but it’s enormous: with 370,000 square meters of rooms and passages, the cavern currently hosts (among other things) a business park, a zipline course, and mountain bike trails, because why not. While DARPA is keeping pretty quiet on the details, I’m guessing that they’ll be taking over a chunk of the cavern and filling it with features representing as many of the environmental challenges as they can.

To learn more about how the SubT Final Event is going to go, we spoke with SubT Program Manager Tim Chung. But first, we talked about Tim’s perspective on the success of the Urban Circuit, and how teams have been managing without an in-person Cave Circuit.

IEEE Spectrum: How did the SubT Urban Circuit go?

Tim Chung: On a couple fronts, Urban Circuit was really exciting. We were in this unfinished nuclear power plant—I’d be surprised if any of the competitors had prior experience in such a facility, or anything like it. I think that was illuminating both from an experiential point of view for the competitors, but also from a technology point of view, too.

One thing that I thought was really interesting was that we, DARPA, didn't need to make the venue more challenging. The real world is really that hard. There are places that were just really heinous for these robots to have to navigate through in order to look in every nook and cranny for artifacts. There were corners and doorways and small corridors and all these kind of things that really forced the teams to have to work hard, and the feedback was, why did DARPA have to make it so hard? But we didn’t, and in fact there were places that for the safety of the robots and personnel, we had to ensure the robots couldn’t go.

It sounds like some teams thought this course was on the more difficult side—do you think you tuned it to just the right amount of DARPA-hard?

Our calibration worked quite well. We were able to tease out and help refine and better understand what technologies are both useful and critical and also those technologies that might not necessarily get you the leap ahead capability. So as an example, the Urban Circuit really emphasized verticality, where you have to be able to sense, understand, and maneuver in three dimensions. Being able to capitalize on their robot technologies to address that verticality really stratified the teams, and showed how critical those capabilities are.

We saw teams that brought a lot of those capabilities do very well, and teams that brought baseline capabilities do what they could on the single floor that they were able to operate on. And so I think we got the Goldilocks solution for Urban Circuit that combined both difficulty and ambition.

Photos: Evan Ackerman/IEEE Spectrum

Two SubT Teams embedded networking equipment in balls that they could throw onto the course.

One of the things that I found interesting was that two teams independently came up with throwable network nodes. What was DARPA’s reaction to this? Is any solution a good solution, or was it more like the teams were trying to game the system?

You mean, do we want teams to game the rules in any way so as to get a competitive advantage? I don't think that's what the teams were doing. I think they were operating not only within the bounds of the rules, which permitted such a thing as throwable sensors where you could stand at the line and see how far you could chuck these things—not only was that acceptable by the rules, but anticipated. Behind the scenes, we tried to do exactly what these teams are doing and think through different approaches, so we explicitly didn't forbid such things in our rules because we thought it's important to have as wide an aperture as possible.

With these comms nodes specifically, I think they’re pretty clever. They were in some cases hacked together with a variety of different sports paraphernalia to see what would provide the best cushioning. You know, a lot of that happens in the field, and what it captured was that sometimes you just need to be up at two in the morning and thinking about things in a slightly different way, and that's when some nuggets of innovation can arise, and we see this all the time with operators in the field as well. They might only have duct tape or Styrofoam or whatever the case may be and that's when they come up with different ways to solve these problems. I think from DARPA’s perspective, and certainly from my perspective, wherever innovation can strike, we want to try to encourage and inspire those opportunities. I thought it was great, and it’s all part of the challenge.

Is there anything you can tell us about what your original plan had been for the Cave Circuit?

I can say that we’ve had the opportunity to go through a number of these caves scattered all throughout the country, and engage with caving communities—cavers clubs, speleologists that conduct research, and then of course the cave rescue community. The single biggest takeaway
is that every cave, and there are tens of thousands of them in the US alone, every cave has its own personality, and a lot of that personality is quite hidden from humans, because we can’t explore or access all of the cave. This led us to a number of different caves that were intriguing from a DARPA perspective but also inspirational for our Cave Circuit Virtual Competition.

How do you feel like the tuning was for the Virtual Cave Circuit?

The Virtual Competition, as you well know, was exciting in the sense that we could basically combine eight worlds into one competition, whereas the systems track competition really didn’t give us that opportunity. Even if we were able have held the Cave Circuit Systems Competition in person, it would have been at one site, and it would have been challenging to represent the level of diversity that we could with the Virtual Competition. So I think from that perspective, it’s clearly an advantage in terms of calibration—diversity gets you the ability to aggregate results to capture those that excel across all worlds as well as those that do well in one world or some worlds and not the others. I think the calibration was great in the sense that we were able to see the gamut of performance. Those that did well, did quite well, and those that have room to grow showed where those opportunities are for them as well.

We had to find ways to capture that diversity and that representativeness, and I think one of the fun ways we did that was with the different cave world tiles that we were able to combine in a variety of different ways. We also made use of a real world data set that we were able to take from a laser scan. Across the board, we had a really great chance to illustrate why virtual testing and simulation still plays such a dominant role in robotics technology development, and why I think it will continue to play an increasing role for developing these types of autonomy solutions.

Photo: Team CSIRO Data 61

How can systems track teams learn from their testing in whatever cave is local to them and effectively apply that to whatever cave environment is part of the final considering what the diversity of caves is?

I think that hits the nail on the head for what we as technologists are trying to discover—what are the transferable generalizable insights and how does that inform our technology development? As roboticists we want to optimize our systems to perform well at the tasks that they were designed to do, and oftentimes that means specialization because we get increased performance at the expense of being a generalist robot. I think in the case of SubT, we want to have our cake and eat it too—we want robots that perform well and reliably, but we want them to do so not just in one environment, which is how we tend to think about robot performance, but we want them to operate well in many environments, many of which have yet to be faced.

And I think that's kind of the nuance here, that we want robot systems to be generalists for the sake of being able to handle the unknown, namely the real world, but still achieve a high level of performance and perhaps they do that to their combined use of different technologies or advances in autonomy or perception approaches or novel mechanisms or mobility, but somehow they're still able, at least in aggregate, to achieve high performance.

We know these teams eagerly await any type of clue that DARPA can provide like about the SubT environments. From the environment previews for Tunnel, Urban, and even Cave, the teams were pivoting around and thinking a little bit differently. The takeaway, however, was that they didn't go to a clean sheet design—their systems were flexible enough that they could incorporate some of those specialist trends while still maintaining the notion of a generalist framework.

Looking ahead to the SubT Final, what can you tell us about the Louisville Mega Cavern?

As always, I’ll keep you in suspense until we get you there, but I can say that from the beginning of the SubT Challenge we had always envisioned teams of robots that are able to address not only the uncertainty of what's right in front of them, but also the uncertainty of what comes next. So I think the teams will be advantaged by thinking through subdomain awareness, or domain awareness if you want to generalize it, whether that means tuning multi-purpose robots, or deploying different robots, or employing your team of robots differently. Knowing which subdomain you are in is likely to be helpful, because then you can take advantage of those unique lessons learned through all those previous experiences then capitalize on that.

As far as specifics, I think the Mega Cavern offers many of the features important to what it means to be underground, while giving DARPA a pretty blank canvas to realize our vision of the SubT Challenge.

The SubT Final will be different from the earlier circuits in that there’s just one 60-minute run, rather than two. This is going to make things a lot more stressful for teams who have experienced bad robot days—why do it this way?

The preliminary round has two 30-minute runs, and those two runs are very similar to how we have done it during the circuits, of a single run per configuration per course. Teams will have the opportunity to show that their systems can face the obstacles in the final course, and it's the sum of those scores much like we did during the circuits, to help mitigate some of the concerns that you mentioned of having one robot somehow ruin their chances at a prize.

The prize round does give DARPA as well as the community a chance to focus on the top six teams from the preliminary round, and allows us to understand how they came to be at the top of the pack while emphasizing their technological contributions. The prize round will be one and done, but all of these teams we anticipate will be putting their best robot forward and will show the world why they deserve to win the SubT Challenge.

We’ve always thought that when called upon these robots need to operate in really challenging environments, and in the context of real world operations, there is no second chance. I don't think it's actually that much of a departure from our interests and insistence on bringing reliable technologies to the field, and those teams that might have something break here and there, that's all part of the challenge, of being resilient. Many teams struggled with robots that were debilitated on the course, and they still found ways to succeed and overcome that in the field, so maybe the rules emphasize that desire for showing up and working on game day which is consistent, I think, with how we've always envisioned it. This isn’t to say that these systems have to work perfectly, they just have to work in a way such that the team is resilient enough to tackle anything that they face.

It’s not too late for teams to enter for both the Virtual Track and the Systems Track to compete in the SubT Final, right?

Yes, that's absolutely right. Qualifications are still open, we are eager to welcome new teams to join in along with our existing competitors. I think any dark horse competitors coming into the Finals may be able to bring something that we haven't seen before, and that would be really exciting. I think it'll really make for an incredibly vibrant and illuminating final event.

The final event qualification deadline for the Systems Competition is April 21, and the qualification deadline for the Virtual Competition is June 29. More details here. Continue reading

Posted in Human Robots

#438779 Meet Catfish Charlie, the CIA’s ...

Photo: CIA Museum

CIA roboticists designed Catfish Charlie to take water samples undetected. Why they wanted a spy fish for such a purpose remains classified.

In 1961, Tom Rogers of the Leo Burnett Agency created Charlie the Tuna, a jive-talking cartoon mascot and spokesfish for the StarKist brand. The popular ad campaign ran for several decades, and its catchphrase “Sorry, Charlie” quickly hooked itself in the American lexicon.

When the CIA’s Office of Advanced Technologies and Programs started conducting some fish-focused research in the 1990s, Charlie must have seemed like the perfect code name. Except that the CIA’s Charlie was a catfish. And it was a robot.

More precisely, Charlie was an unmanned underwater vehicle (UUV) designed to surreptitiously collect water samples. Its handler controlled the fish via a line-of-sight radio handset. Not much has been revealed about the fish’s construction except that its body contained a pressure hull, ballast system, and communications system, while its tail housed the propulsion. At 61 centimeters long, Charlie wouldn’t set any biggest-fish records. (Some species of catfish can grow to 2 meters.) Whether Charlie reeled in any useful intel is unknown, as details of its missions are still classified.

For exploring watery environments, nothing beats a robot
The CIA was far from alone in its pursuit of UUVs nor was it the first agency to do so. In the United States, such research began in earnest in the 1950s, with the U.S. Navy’s funding of technology for deep-sea rescue and salvage operations. Other projects looked at sea drones for surveillance and scientific data collection.

Aaron Marburg, a principal electrical and computer engineer who works on UUVs at the University of Washington’s Applied Physics Laboratory, notes that the world’s oceans are largely off-limits to crewed vessels. “The nature of the oceans is that we can only go there with robots,” he told me in a recent Zoom call. To explore those uncharted regions, he said, “we are forced to solve the technical problems and make the robots work.”

Image: Thomas Wells/Applied Physics Laboratory/University of Washington

An oil painting commemorates SPURV, a series of underwater research robots built by the University of Washington’s Applied Physics Lab. In nearly 400 deployments, no SPURVs were lost.

One of the earliest UUVs happens to sit in the hall outside Marburg’s office: the Self-Propelled Underwater Research Vehicle, or SPURV, developed at the applied physics lab beginning in the late ’50s. SPURV’s original purpose was to gather data on the physical properties of the sea, in particular temperature and sound velocity. Unlike Charlie, with its fishy exterior, SPURV had a utilitarian torpedo shape that was more in line with its mission. Just over 3 meters long, it could dive to 3,600 meters, had a top speed of 2.5 m/s, and operated for 5.5 hours on a battery pack. Data was recorded to magnetic tape and later transferred to a photosensitive paper strip recorder or other computer-compatible media and then plotted using an IBM 1130.

Over time, SPURV’s instrumentation grew more capable, and the scope of the project expanded. In one study, for example, SPURV carried a fluorometer to measure the dispersion of dye in the water, to support wake studies. The project was so successful that additional SPURVs were developed, eventually completing nearly 400 missions by the time it ended in 1979.

Working on underwater robots, Marburg says, means balancing technical risks and mission objectives against constraints on funding and other resources. Support for purely speculative research in this area is rare. The goal, then, is to build UUVs that are simple, effective, and reliable. “No one wants to write a report to their funders saying, ‘Sorry, the batteries died, and we lost our million-dollar robot fish in a current,’ ” Marburg says.

A robot fish called SoFi
Since SPURV, there have been many other unmanned underwater vehicles, of various shapes and sizes and for various missions, developed in the United States and elsewhere. UUVs and their autonomous cousins, AUVs, are now routinely used for scientific research, education, and surveillance.

At least a few of these robots have been fish-inspired. In the mid-1990s, for instance, engineers at MIT worked on a RoboTuna, also nicknamed Charlie. Modeled loosely on a blue-fin tuna, it had a propulsion system that mimicked the tail fin of a real fish. This was a big departure from the screws or propellers used on UUVs like SPURV. But this Charlie never swam on its own; it was always tethered to a bank of instruments. The MIT group’s next effort, a RoboPike called Wanda, overcame this limitation and swam freely, but never learned to avoid running into the sides of its tank.

Fast-forward 25 years, and a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) unveiled SoFi, a decidedly more fishy robot designed to swim next to real fish without disturbing them. Controlled by a retrofitted Super Nintendo handset, SoFi could dive more than 15 meters, control its own buoyancy, and swim around for up to 40 minutes between battery charges. Noting that SoFi’s creators tested their robot fish in the gorgeous waters off Fiji, IEEE Spectrum’s Evan Ackerman noted, “Part of me is convinced that roboticists take on projects like these…because it’s a great way to justify a trip somewhere exotic.”

SoFi, Wanda, and both Charlies are all examples of biomimetics, a term coined in 1974 to describe the study of biological mechanisms, processes, structures, and substances. Biomimetics looks to nature to inspire design.

Sometimes, the resulting technology proves to be more efficient than its natural counterpart, as Richard James Clapham discovered while researching robotic fish for his Ph.D. at the University of Essex, in England. Under the supervision of robotics expert Huosheng Hu, Clapham studied the swimming motion of Cyprinus carpio, the common carp. He then developed four robots that incorporated carplike swimming, the most capable of which was iSplash-II. When tested under ideal conditions—that is, a tank 5 meters long, 2 meters wide, and 1.5 meters deep—iSpash-II obtained a maximum velocity of 11.6 body lengths per second (or about 3.7 m/s). That’s faster than a real carp, which averages a top velocity of 10 body lengths per second. But iSplash-II fell short of the peak performance of a fish darting quickly to avoid a predator.

Of course, swimming in a test pool or placid lake is one thing; surviving the rough and tumble of a breaking wave is another matter. The latter is something that roboticist Kathryn Daltorio has explored in depth.

Daltorio, an assistant professor at Case Western Reserve University and codirector of the Center for Biologically Inspired Robotics Research there, has studied the movements of cockroaches, earthworms, and crabs for clues on how to build better robots. After watching a crab navigate from the sandy beach to shallow water without being thrown off course by a wave, she was inspired to create an amphibious robot with tapered, curved feet that could dig into the sand. This design allowed her robot to withstand forces up to 138 percent of its body weight.

Photo: Nicole Graf

This robotic crab created by Case Western’s Kathryn Daltorio imitates how real crabs grab the sand to avoid being toppled by waves.

In her designs, Daltorio is following architect Louis Sullivan’s famous maxim: Form follows function. She isn’t trying to imitate the aesthetics of nature—her robot bears only a passing resemblance to a crab—but rather the best functionality. She looks at how animals interact with their environments and steals evolution’s best ideas.

And yet, Daltorio admits, there is also a place for realistic-looking robotic fish, because they can capture the imagination and spark interest in robotics as well as nature. And unlike a hyperrealistic humanoid, a robotic fish is unlikely to fall into the creepiness of the uncanny valley.

In writing this column, I was delighted to come across plenty of recent examples of such robotic fish. Ryomei Engineering, a subsidiary of Mitsubishi Heavy Industries, has developed several: a robo-coelacanth, a robotic gold koi, and a robotic carp. The coelacanth was designed as an educational tool for aquariums, to present a lifelike specimen of a rarely seen fish that is often only known by its fossil record. Meanwhile, engineers at the University of Kitakyushu in Japan created Tai-robot-kun, a credible-looking sea bream. And a team at Evologics, based in Berlin, came up with the BOSS manta ray.

Whatever their official purpose, these nature-inspired robocreatures can inspire us in return. UUVs that open up new and wondrous vistas on the world’s oceans can extend humankind’s ability to explore. We create them, and they enhance us, and that strikes me as a very fair and worthy exchange.

This article appears in the March 2021 print issue as “Catfish, Robot, Swimmer, Spy.”

About the Author
Allison Marsh is an associate professor of history at the University of South Carolina and codirector of the university’s Ann Johnson Institute for Science, Technology & Society. Continue reading

Posted in Human Robots