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.

Comments

Re:That's exactly how Terminator got started

[freddy_dreddy]

http://www.symbrion.eu/

UCAR

[DustyShadow]

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.

Re:So Mr. Ng makes semi-autonomous mini-helicopter

[Anonymous Coward]

It looks like someone with mod points has never read Snowcrash.

Re:Autonomous

[pete-classic]

Your blithe refusal to even acknowledge the article is an inspiration, sir.

It might seem that an autonomous helicopter could fly stunts by simply replaying the exact finger movements of an expert pilot using the joy sticks on the helicopter's remote controller. That approach, however, is doomed to failure because of uncontrollable variables such as gusting winds.

-Peter

Re:Helicopter macro recording?

[Czyl]

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.

youtube "rc helicopter".

[bronney]

and you'll see. Throw in a little wind here and there and the robot doesn't stand a chance.

http://ca.youtube.com/watch?v=gi7G-VzU2r4

reinforcement learning vs. simulation

[heroine]

This story got a lot more attention than the other zillions of autonomous helicopters out there. The disappointment with the Stanford one is it is reinforcement learning. It's recording and playing the commands of a human pilot instead of simulating a dynamic model and deducing commands based on a genetic algorithm. The real value in ground based autopilot is having enough computing power to use biological algorithms.

Re:reinforcement learning vs. simulation

[Kryos]

It's recording and playing the commands of a human pilot instead of simulating a dynamic model and deducing commands based on a genetic algorithm.

Or, you could RTFA.

As Oku repeated a maneuver several times, the trajectory of the helicopter inevitably varied slightly with each flight. But the learning algorithms created by Ng's team were able to discern the ideal trajectory the pilot was seeking. Thus the autonomous helicopter learned to fly the routine better - and more consistently - than Oku himself.