More Robust Gripping
This year was also notable for big advances in grasping technology: simple, fast systems that let robots grab new objects quickly and robustly, using relatively simple hands. Such systems could help improve stand-alone robots and prosthetics. Researchers at Columbia University found that by giving a robotic hand the same limits in dexterity as a human hand, they could make a more efficient device (“Helping Robots Get a Grip”). A group at Harvard and Yale universities also found value in simplicity: its soft plastic hand–embedded with just a few sensors–could pick up unknown objects using a flexible grip (“A Simpler, Gentler Robotic Grip”). A new implant could also bring improvements by giving patients unprecedented control over fine movements of prosthetics ( “Seamlessly Melding Man and Machine”).
On a larger scale, NASA’s new robotic arm could help astronauts by rotating and lifting heavy objects (“A Robotic Arm for Lunar Missions”).
Getting Around: Jogging, Squishing, and Soaring Bots
Boston Dynamics, the engineering company behind BigDog, gave a stunning demonstration this year of its realistic, two-legged Petman robot, which the military will use to test chemical suits (“Meet BigDog’s Two-Legged Brother”).
iRobot released a new video of another robot funded by the U.S. Defense Advanced Research Projects Agency. The Chembot, a deceptively simple-looking blob, will be able to squeeze under doors or through tiny openings, most likely for military surveillance (“iRobot Adds to a Shape-Shifting Robot Menagerie”). Other surveillance robots featured this year include a tiny flier that mimics how a maple seed falls (“Micro-Vehicle Imitates the Winged Maple Seed”) and a new sense-and-avoid visual system for unmanned aerial robots (“How to Make UAVs Fully Autonomous”).
Other robots for home and work also made advances in mobility; a robot developed by a consortium in Europe uses a system based on how a person processes visual information to navigate a cluttered environment. The technology could one day be used for a smart wheelchair (“A Robot that Navigates Like a Person”). Another robot from Brown University learned how to follow a person at a set distance, almost like a well-trained dog, by using a new, infrared image-recognition program (“Robot Plays Follow the Leader”).
When designing an embedded system choosing which tools to use often comes down to building a custom solution or buying off-the-shelf tools.