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Proceedings Paper

Global and local obstacle avoidance technique for an autonomous vehicle
Author(s): Keith W. Gray; Kevin S. Saunders
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Paper Abstract

The Center for Self-Organizing and Intelligent Systems (CSOIS) is engaged in developing autonomous ground vehicles. A significant problem for such vehicles is obstacle detection and avoidance. After studying various methods of detection, a scanning laser system was chosen that can detect objects at a distance of up to thirty feet while traveling between five and ten miles per hour. Once an object is detected, the vehicle must avoid it. The project employs a mission-level path planner that predetermines the path of a vehicle. One avoidance scheme is to inform the path planner of the obstacle and then let it re-plan the path. This is the global approach to the problem, which allows the use of existing software for maneuvering the vehicle. However, replanning is time consuming and lacks knowledge of the entire obstacle. An alternative approach is to use local avoidance, whereby a vehicle determines how to get by an obstacle without help from the path planner. This approach offers faster response without requiring the computing resource of the path planner. The disadvantage is that during local avoidance the vehicle ignores the global map of known obstacles and does not know to turn control back to the path planner if mission efficiency is adversely affected. This paper will describe a method for combining the current global path planner with a local obstacle avoidance technique to efficiently complete required tasks in a partially unknown environment.

Paper Details

Date Published: 22 July 1999
PDF: 12 pages
Proc. SPIE 3693, Unmanned Ground Vehicle Technology, (22 July 1999); doi: 10.1117/12.354446
Show Author Affiliations
Keith W. Gray, Utah State Univ. (United States)
Kevin S. Saunders, Utah State Univ. (United States)

Published in SPIE Proceedings Vol. 3693:
Unmanned Ground Vehicle Technology
Grant R. Gerhart; Robert W. Gunderson; Chuck M. Shoemaker, Editor(s)

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