Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

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

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. Such a system can be embedded in a general, multi-level perception/control system.
Proceedings Title
Proceedings of the 13th International Conference on Pattern Recognition Applications and Robotic Systems
Conference Dates
August 1, 1996
Conference Location
Vienna, AU
Conference Title
Pattern Recognition Applications and Robotic Systems

Keywords

Vision, Robotics & Intelligent Systems, Unmanned Systems, Mobility, active vision, mobile robots, obstacle avoidance, real-time systems, real-time vision

Citation

Camus, T. , Coombs, D. , Herman, M. and , T. (1996), Real-Time Single-workstation Obstacle Avoidance Using Only Wide-Field Flow Divergence, Proceedings of the 13th International Conference on Pattern Recognition Applications and Robotic Systems, Vienna, AU, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=820562 (Accessed April 19, 2024)
Created August 1, 1996, Updated February 17, 2017