Thaindian News

Washington, Sep 3 (IANS) Computer scientists have developed an artificial intelligence system that enables robotic choppers to teach themselves difficult stunts by watching other airborne helicopters. The stunts are “by far the most difficult aerobatic manoeuvers 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 at the Stanford University.

There is interest in using autonomous helicopters to search for land mines in war-torn areas or to map out the hot spots of California wildfires in real time, allowing firefighters to quickly move toward or away from them. Firefighters now must often act on information that is several hours old, Abbeel said.

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.

Stanford’s artificial intelligence (AI) system learned how to fly by “watching” the four-foot-long helicopters flown by expert radio control pilot Garett Oku.

“Garett can pick up any helicopter, even ones he’s never seen, and go fly amazing aerobatics. So the question for us is always, why can’t computers do things like this?” Coates said.

Computers can, it turns out. On a recent morning in an empty field at the edge of campus, Abbeel and Coates sent up one of their helicopters to demonstrate autonomous flight. The aircraft, brightly painted Stanford red, is an off-the-shelf radio control helicopter, with instrumentation added by the researchers.

For five minutes, the chopper, on its own, ran through a dizzying series of stunts beyond the capabilities of a full-scale piloted helicopter and other autonomous remote control helicopters.

The AI helicopter performed a smorgasbord of difficult manoeuvres: travelling flips, rolls, loops with pirouettes, stall-turns with pirouettes, a knife-edge, an Immelmann, a slapper, an inverted tail slide and a hurricane, described as a “fast backward funnel.”

“I think the range of manoeuvres they can do is by far the largest” in the autonomous helicopter field, said Eric Feron, a Georgia Tech aeronautics and astronautics professor who worked on autonomous helicopters while at MIT.

“But what’s more impressive is the technology that underlies this work. In a way, the machine teaches itself how to do this by watching an expert pilot fly. This is amazing.”

Writing software for robotic helicopters is a daunting task, in part because the craft itself, unlike an airplane, is inherently unstable. “The helicopter doesn’t want to fly. It always wants to just tip over and crash,” said Oku, the pilot.

Early on, Abbeel and Coates attempted to write computer code that would specify the commands for the desired trajectory of a helicopter flying a specific manoeuvre. While this hand-coded approach succeeded with novice-level flips and rolls, it flopped with the complex tic-toc.”

The helicopter carries accelerometers, gyroscopes and magnetometers, the latter of which use the Earth’s magnetic field to figure out which way the helicopter is pointed.