Heartland Robotics is a company headed by legendary iRobot co-founder Rodney Brooks. It’s been in ‘stealth mode’ since its founding in 2008, meaning that they’re working on something cool enough to have raised some $32 million in funding, but they’re not ready to tell the world about it yet.

With the latest round of funding (which involves as bunch of investors being shown around and told what the plan is), some new information has leaked out from Heartland, and it’s tantalizing:

Visitors to Heartland describe a robot that looks like a human from the waist up, with a torso; either one or two arms with grippers; and a camera where you might expect the head to be. The robot is on a rolling base rather than legs; it can be moved around but doesn’t move autonomously. The arm and gripper can be quickly trained to do a repetitive task just by moving them, no software code required.

It’s possible that this robot is based in part on MIT’s Obrero platform, pictured above. There’s more:

“Brooks apparently likens Heartland’s robot, which is intended to perform assembly and packaging tasks that low-wage factory workers do today, to Apple’s iPhone. He’s interested in encouraging a community of software developers to create applications that would teach the robot to do tasks such as using its camera to recognize a defective widget and pulling it off the conveyor belt.”

Thinking about robots as hardware that runs apps is not unique to Heartland, but the deciding factor could be the target price point: a shockingly low $5000. At that level, it’s easy for businesses to justify purchasing a robot just to try it out, since the risk is so small. And if they can set the robot up on an assembly line (which seems to be its general target market), it could very rapidly start making things more efficient for even small businesses, especially if the robot is as easy to program as they’re trying to make it.

Even if it takes three of these robots to do the job of one human, you’re still talking about a very positive investment. Heck, even if you needed ten of them, a $5k a pop they’d probably pay for themselves in less than a year when you consider the overhead that humans require, and they’d work 24/7 to boot.

For a long (long long LONG) time, the robotics industry has been looking for its PC, the one killer platform or application that has the potential to make robots simple, cheap, reliable, and useful. It hasn’t turned out to be vacuums, but it might just be a cheap robot worker from Heartland.

Stay tuned.

[ Heartland Robotics ] VIA [ Boston.com ] and [ NBF ]

Legged robots offer a lot more flexibility than wheeled robots do when it comes to moving over uneven terrain, like the types of surfaces you might expect to find on the moon. As the Apollo astronauts discovered, however, walking on the moon is much easier said than done, and the most effective bipedal gait turned out to be a sort of robot-unfriendly bouncy trotting run.

While low gravity sounds like it would be great for walking robots (easier on the motors, more time to recover), it’s actually not ideal, since the robot would spend most of its time not in direct contact with the ground as it tried to move. And running like the human astronauts did wouldn’t be much better because of the difficulty of keeping the robot consistently stable. Researchers at Waseda University in Tokyo have developed a computer model that suggests a new way for lunar robots to get around: jumping. Based on the model, the most stable and efficient way for a bipedal robot like their WABIAN-2R to conquer the moon would be with a series of foot-together, one meter high jumps.

Japan, if you remember, is already planning to put humanoid robots on the moon by 2020 to do some rock gardening. This is totally cool, but when it comes down to it, a humanoid might not be the best platform for planetary exploration. Yes, humanoids are better than wheeled robots in certain situations, but there are plenty of designs that offer most of the adaptability of legs while preserving the efficiency and stability of a wheeled platform. Giant mutant PackBot, anyone?

[ WABIAN-2R ] VIA [ New Scientist ]

What’s the best way to test out the robustness of your robot’s navigation system? Just set it loose to wander around the office for a week and see what happens. 70 kilometers later, this PR2 ended up with a funny hat, some stickers, and a new sense of confidence.

For 7 days, the PR2 was assigned to autonomously navigate the Willow Garage offices, locating outlets and recharging itself when necessary. If it got stuck, it was allowed to text a human for help, and that human could use a website to help the PR2 out. In 70 kilometers, this only happened twice (twice!), and I’m more than a little curious as to what those circumstances were. Apparently, this PR2 is still clocking in the kilometers, and the data it’s collecting on robust navigation will be made available to the ROS community.

In other PR2 news, Willow Garage has just sold their first four PR2 units to CNRS Laboratory of Analysis and Architecture of Systems (LAAS-CNRS) in Toulouse, France; George Washington University in Washington, DC; Samsung Electronics in Suwon, Korea; and University of Washington in Seattle, WA. This is good for them financially, of course, but the important thing is that institutions are taking PR2 and ROS (and what they stand for) seriously enough to shell out major cash to get a high quality piece of the action. It’s one thing to give away a bunch of robots and call them a success; it’s another thing when people believe in your product and what you’re doing enough to invest hundreds of thousands of dollars in your concept. Congrats to Willow Garage, and may they sell enough PR2s to drive the cost down to the point where I can afford one.

[ Willow Garage ]

You probably don’t remember, but back in 2007 (which is forever ago, I know) we posted about a jumping robot called Mowgli from the University of Tokyo. This most recent video shows how Mowgli has evolved from a jumping frog to a jumping humanoid called Athlete, with some running (ish) thrown in for good measure.

Now, the running is obviously not entirely stable. But it’s pretty remarkable just how human-y Athlete appears, even as it’s falling. The reason for this is Athlete’s construction, which uses air muscles, limbs, and a joint structure specifically designed to mimic that of a human.

Generally, I’m not in favor of biomimicry if an alternate robotic system is capable of doing the same kinds of things more efficiently. Humans, though, have had a long time to get bipedal walking figured out, and even beyond humans, animals have ended up with the same basic leg structure, so it must work pretty well. In this case, specifically, the human model seems to have clear advantages over other running robots like ASIMO, for whom barely running seems to be at the technical limit of its movement capabilites.

To get Athlete to keep running, its foot sensors and inertial sensors need to provide feedback to the air muscles a bit faster. Researchers are optimistic that with a few tweaks, Athlete will be able to develop a stable sprinting gait, which (let’s face it) would be pretty amazing.

VIA [ IEEE ]

The robot juggling gauntlet has been thrown down, and commenter Noah produced this video from the early 90s showing a robot juggling two balls using real time visual feedback. The 90s is practically prehistoric in robot years, and apparently this guy could keep two balls in the air for hours at a time.

I’m definitely impressed. Anyone got any more?

Paul posted a comment on that single ball juggling quadrotor video from yesterday to tip us off to a robot from his lab at the University of Washington that can juggle two balls. It’s not juggling while flying, but arguably that takes even more skill, since a stationary platform (especially one that doesn’t tilt) is less tolerant of variation. And managing to juggle two ping pong balls using a platform that size is damn impressive.

Okay, so the gauntlet has been thrown down. Who’s working on a robot that can juggle three balls?

[ UW Movement Control Lab ]

We wrote about robotic road trains last year, and somewhat remarkably, the research project that’s trying to make them happen is progressing nicely with help fro companies like Volvo. Cars drafting closely behind trucks in road trains save up to 40% in fuel consumption, thereby saving money and the environment at the same time. But the biggest advantage of being in a road train is that you can just stop paying attention to the road and do something else while your car drives itself.

It’s true that your life is in the hands of the system, and not in your hands, but while the current perception is that that makes things more dangerous, it really should be the exact opposite. With your car doing all the hard work for you, accidents are less likely.

Of course, the system is only as safe as the lead driver, so many different technologies are being employed to make sure that the person driving the truck is sober, qualified, and paying attention. This includes a breathalyzer and a fancy infrared camera system for vision tracking to make sure that the driver is paying attention to the road.

Other especially exciting bits from the video include mentions of ‘several years from now’ for road trains themselves, and the suggestion that technology to allow cars to drive themselves in stop and go traffic jams might be just around the corner. As we’ve discussed before, the technology (adaptive full stop cruise control and lane keeping) is already here and in some cars, we just have to catch up in terms of people (and lawyers) being comfortable with it.

VIA [ Wired ]

Wow. Unlike that blind robot juggler, this quadrotor is juggling one ball the hard way, with a tennis racket duct-taped to itself. Someone just needs to toss a couple more balls in there and see what happens…

[ ETH Zurich Flying Arena ]

Kinect’s 3D sensor is so cheap and effective that it’s getting bolted onto any robot that moves, and quadrotors are just the latest victims. UC Berkeley’s quadrotor is using the Kinect for autonomous flight and dynamic obstacle avoidance, and as long as you don’t come at it from behind, it works great. The nice thing about using Kinect like this is that it translates into a SLAM system, where the robot can fly around and make a 3D map of a space using the same data that it’s relying on to keep from crashing in to stuff.

[ UC Berkeley Hybrid Systems Lab ] VIA [ Trossen ]

Norri from GetRobo had a chance to sit down with Sebastian Thrun, Christopher Urmson, and Anthony Levandowski, three of the guys who have been working with Google to develop their autonomous Priuses. Here’s a teaser:

What are the things that the Google car can do now that were not possible at the Urban Challenge?

There’s a lot. Drive at freeway speed. None of the vehicles we had at the Urban Challenge could do that. We can now perceive pedestrians and deal with them. We can merge with freeway traffic. None of the Urban Challenge vehicles you would want to see driving on a public road with traffic. They were very cautious, they were kinda jerky. With our vehicle, you can operate around other traffic. Even people who are videotaping as they go by think that there’s a human driving. And that’s a quality that we didn’t have before.

Head over to GetRobo (or pick up a copy of the Japan edition of the Wall Street Journal) to check out the rest of the interview, including some super interesting bits where they explain some of the specific points where the autonomous technology is not quite up to snuff. I’m just going to toss in one more quote from the interview, though, because it is so directly relevant to why all of this robot car stuff is important in the first place:

What is the ideal way that the public can benefit from your research?

The end goal is pretty clear. Today we have close to 40,000 people in the U.S. that are involved in traffic accidents each year. More than a million people worldwide. The American commuter spends 52 minutes in traffic so we would like to make this safer, more fun and productive. We can envision that our technology will assist people with disabilities, people who can’t be mobile and people who lose ability to drive due to aging. So that is the vision.

[ GetRobo ]