Real-time Single-workstation Obstacle Avoidance Using Only Wide-field Flow Divergence



AUTHORS: Ted Camus, Dave Coombs, Marty Herman, Tsai Hong

AFFILIATION: Perception Systems Group, Intelligent Systems Division National Institute of Standards and Technology

ABSTRACT:

A real-time robot vision system is described which uses only the divergence of the optical flow field for both steering control and collision detection. The robot has wandered about the lab at 20 cm/s for as long as 26 minutes without collision. The entire system is implemented on a single ordinary UNIX workstation without the benefit of real-time operating system support. Dense optical flow data are calculated in real-time across the entire wide-angle image. The divergence of this optical flow field is calculated everywhere and used to control steering and collision behavior. Divergence alone has proven sufficient for steering past objects and detecting imminent collision. The major contribution is the demonstration of a simple, robust, minimal system that uses flow-derived measures to control steering and speed to avoid collision in real time for extended periods.