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.