Dal Robotic Locomotion Grup del MIT computer science and artificial intelligence laboratori (CSAIL) vi propongo il filmato di LittleDog un robot quadrupede in grado di percepire la struttura degli ostacolini che incontra ed adattare il suo movimento.
Researchers at places like MIT have been using Boston Dynamics‘ LittleDog robot for years now as a testbed to teach legged robots to learn how to traverse variable terrain on their own. This video shows some highlights of a “dynamic double-support gait,” which means (as near as I can tell) that LittleDog is supporting itself, at times, on only two of its four legs. This is a substantially more efficient way of negotiating terrain than we first saw two years ago. LittleDog also demonstrates some markedly biological ways of negotiating obstacles (with the possible exception of the belly flop on the Jersey barrier)… I especially liked how it pranced in place slightly before tackling each stair. All this stuff is obviously a lot of work for a little bot, since poor LittleDog completely collapses at the end of every test.
LittleDog, remember, is teaching itself the most efficient way to negotiate these surfaces. Overhead cameras examine the terrain and plan out LittleDog’s route by computing a ‘cost’ for each step, which takes into account the distance moved towards the goal as well as the potential for a fall. After a lot of trial and error, LittleDog figures out how to best compromise between progress and stability, and the lessons it learns could be propagated up to other, larger quadruped robots.
This video is from Phase 2 of DARPA’s Learning Locomotion program… MIT’s LittleDog team was awarded funding for Phase 3 of this program back in 2008, so we’ll keep you updated.