A fleet of scale-model autonomous helicopters operated by Stanford computer scientists can learn to fly complex stunts by "watching" other helicopters perform the same maneuvers, the research team said this week. The project illustrates the capability of "apprenticeship learning," in which robots learn by observing an expert, rather than by following pre-programmed software instructions. Using artificial intelligence, the autonomous helicopters are able to fly a complex routine while correcting for variables such as wind gusts. During a flight, instruments monitor the position, direction, orientation, velocity, acceleration and spin of the helicopter in several dimensions. A computer crunches the data, makes quick calculations, and beams new flight directions to the helicopter via radio 20 times per second -- with no human input. The technology could be useful in "training" autonomous helicopters to search for land mines or wildfires, said Andrew Ng, director of the Stanford research team.
This is a companion discussion topic for the original entry at https://www.avweb.com/news/autonomous-helicopters-teach-themselves-aerobatics