Stanford's "Autonomous" Helicopters Learn
An anonymous reader writes "Stanford computer scientists have developed an artificial intelligence system that enables robotic helicopters to teach themselves to fly difficult stunts by 'watching' other helicopters perform the same maneuvers. The result is an autonomous helicopter that can perform a complete airshow of complex tricks on its own. The stunts are 'by far the most difficult aerobatic maneuvers flown by any computer controlled helicopter,' said Andrew Ng, the professor directing the research of graduate students Pieter Abbeel, Adam Coates, Timothy Hunter and Morgan Quigley. The dazzling airshow is an important demonstration of 'apprenticeship learning,' in which robots learn by observing an expert, rather than by having software engineers peck away at their keyboards in an attempt to write instructions from scratch.'" The title of the linked article uses the term "autonomous," but that's somewhat misleading. The copters can't fly on their own, but rather can duplicate complex maneuvers learned from a human pilot.
DARPA had a project going on for awhile called UCAR, which was an unmanned autonomous combat helicopter. Unfortunately the war took all the money and DARPA had to cancel the competitions between Lockheed and Northrop.
Northrop currently has an unmanned helicopter called Firescout that has autonomously landed on a Navy ship while the ship was moving.
My point is that this type of work is nothing new.
Your blithe refusal to even acknowledge the article is an inspiration, sir.
-Peter
It's actually considerably more difficult. Unlike your computer, the helicopter encounters different environmental conditions each time it flies, so that just blindly recording the controller inputs and replaying them will cause the helicopter to crash. The trick in apprenticeship learning is to learn the flying model used by the pilot, not just recording and replaying a macro.