Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover

摘要

The Stanford AI Lab cart is a card-table sized mobile robot controlled remotely through a radio link, and equipped with a TV camera and transmitter. A computer has been programmed to drive the cart through cluttered indoor and outdoor spaces, gaining its knowledge of the world entirely from images broadcast by the onboard TV system. The cart uses several kinds of stereo to locate objects around it in 3D and to deduce its own motion. It plans an obstacle avoiding path to a desired destination on the basis of a model built with this information. The plan changes as the cart perceives new obstacles on its journey. The system is reliable for short runs, but slow. The cart moves one meter every ten to fifteen minutes, in lurches. After rolling a meter it stops, takes some pictures and thinks about them for a long time. Then it plans a new path, executes a little of it, and pauses again. The program has successfully driven the cart through several 20 meter indoor courses (each taking about five hours) complex enough to necessitate three or four avoiding swerves. A less successful outdoor run, in which the cart skirted two obstacles but collided with a third, was also done. Harsh lighting (very bright surfaces next to very dark shadows) giving poor pictures and movement of shadows during the cart's creeping progress were major reasons for the poorer outdoor performance. The action portions of these runs were filmed by computer controlled cameras. (Author)