Online-learning and Attention-based Obstacle Avoidance Using a Range Finder

May 2004

Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)

Volume

Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)

All Papers

We considered the problem of developing local reactive obstacle-avoidance behaviors by a mobile robot through online real-time learning. The robot operated in an unknown bounded 2-D environment populated by static or moving obstacles (with slow speeds) of arbitrary shape. The sensory perception was based on a laser range finder. We presented a learning-based approach to the problem. To greatly reduce the number of training samples needed, an attentional mechanism was used. An efficient, real-time implementation of the approach had been tested, demonstrating smooth obstacle-avoidance behaviors in a corridor with a crowd of moving students as well as static obstacles.