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

Published

Author(s)

Theodore(Ted) Camus, David Coombs, Martin Herman, Tsai Hong Hong

Abstract

This paper describes a real-time robot vision system 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- avoidance 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. Such a system can be embedded in a general, multi-level perception/control system.
Citation
Videre: Journal of Computer Vision Research
Volume
1, No. 3

Keywords

Vision, Mobility, Control, Unmanned Systems, computer vision, image flow divergence, motion analysis, obstacle avoidance

Citation

Camus, T. , Coombs, D. , Herman, M. and , T. (1999), Real-time Single-workstation Obstacle Avoidance Using Only Wide-field Flow Divergence, Videre: Journal of Computer Vision Research, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=820637 (Accessed April 19, 2024)
Created January 1, 1999, Updated February 17, 2017