The Future Is Here Today...Robots, Genetics, AI, Longevity, Singularity

MIT Helps Little Dog Navigate Rough Terrain

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by Aaron Saenz on September 15th, 2009
MIT is teaching Little Dog new tricks in navigation.

MIT is teaching Little Dog new tricks in navigation.

Sometimes robot videos just make me laugh. CSAIL at MIT has been working with Boston Dynamics’ robot Little Dog, helping it navigate rough terrain in novel ways. The scrappy quadruped can dynamically shifts its weight on two legs at a time, helping it climb slopes and stairs, and generally get around.And as soon as Little Dog gets where it’s going, it promptly flops down on its belly much like a real canine. The careful steps followed by exhausted collapse gets me every time. Check out the video from BotJunkie below, and look towards the end (1:44) to see for yourself.

Little Dog’s journey is part of Phase 2 of DARPA’s Learning Locomotion Program. As those who read our War 2.0 story know, a larger version of the robot, aptly named Big Dog, is being bred to work as a mule for soldiers in the field. That bot can haul loads and keep walking even after a hefty kick (see its video below). The navigating and stepping routines that CSAIL teaches Little Dog are going to be directly portable over to Big Dog.
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ASIMO robot impresses by navigating changing terrain

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by Aaron Saenz on August 10th, 2009

Scientists are helping robots think before they step. Honda’s versatile ASIMO robot was able to find its way through moving obstacles and simulated terrain at Carnegie Mellon University. It makes you wonder if the researchers spent a lot of hours in video arcades during the 80s. If so, it was time well spent because ASIMO performed like a dream, navigating around cut out shapes that represented real-world barriers. Able to dodge spinning blades, Frogger-like moving lines, and dynamic environments, ASIMO showed us again why its one of the top humanoid bots out there. Watch our robot friend outperform the frog in a Discovery Channel video after the break.

Wait...now go!..No! Wait...wait...go, go, go!

Wait...now go!..No! Wait...wait...go, go, go!

ASIMO’s success may prove to be a launching point for walking robots. Bipedal bots are some of the most challenging designs in the robotics world. Not only do you have to worry about balance and locomotion, they have to find a safe place to put their feet. Which is why ASIMO’s performance was so exemplary. Carnegie Mellon’s new foot-stepping software allows the bot to plan out complex and dynamic paths in its environment. It is constantly asking itself, what’s the best way to get where I’m going?

Of course, ASIMO wasn’t alone. Carnegie Mellon’s Robotics Institute developed a generalized foot stepping program for all legged robots, not just Honda’s. The Linux based H7, the HRP-2 series (remember the sexy 4C that we covered early?), and even the “little dog” (we featured the “big dog” in our war robots story) had a chance to find their way through difficult terrain and elevations. Each robot had its own course, and its own videos, but only ASIMO seemed poised to step out in the real world.

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The Lost Robot Saga Continues: Munich

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by Aaron Saenz on May 19th, 2009

You think that these robots would start investing in a GPS system. Recently, Singularity Hub covered the Tweenbot, a simple cardboard-wrapped automaton that was guided through New York City by the hands of New Yorkers. The next step in the lost robot evolution has appeared: Autonomous City Explorer (or ACE) a robot that navigated the mean streets of Munich just like any tourist would: by asking directions from the natives. ACE identified and queried people around it to point it in the right direction, and, against my most cynical expectations, it arrived safely and sound at its destination. (Check out the video from New Scientist and the end of the post)

Autonoumous City Explorer (ACE) navigated Munich by the friendly finger-pointing of humans.

Autonoumous City Explorer (ACE) navigated Munich by the friendly finger-pointing of humans.

So what makes this lost robot so unique? Unlike its tween counterpart, ACE isn’t just picked up and pushed in the right direction. The bot is roughly human sized and packed with instruments to help it detect and query humans for help. First, there are cameras and image recognition software geared towards finding people and moving ACE towards them. When a human is found, an audio message is played while virtual lips move on a screen. If the human is friendly (aren’t we all?) he or she uses a touch-screen to indicate it’s willingness to give directions. The human will then point in the direction ACE should go.

And ACE follows your finger! That’s really kind of cool. By using multiple cameras and more image software, ACE is able to build a 3D model of the human and where he or she is actually pointing to. Compared to a toddler, this isn’t a remarkable skill, but following visual cues is really difficult for most robots out there. ACE also prompts its helper human to use the touch-screen to suggest a given path, but in the end, it can rely on just the pointing.

ACE’s point and go navigation avoids the hassle of interpreting humanity’s subjective audible directions. “It’s over there, behind that building, then you sort of take a right and keep going for a while.” —that’s a message fit to make a robot pull its hair out. ACE just has to query enough people (38 for its maiden voyage) and it will build up a developing map of its surroundings. Simple and effective, the ACE system allowed the robot to travel little more than 1km in 5 hours. Not a speedy journey, but very promising.

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