Share Email Print

Proceedings Paper

Synthesis of reflexive algorithms with intelligence for effective robot path planning in unknown environments
Author(s): Markus A. Wolfensberger; Donald Wright
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The ability of a robot to find a goal in an unknown environment is significantly improved from previous path planners with the synthesis of intelligence and reflexive algorithms as a path planning approach. A hybrid expert system vector field (HESV) path planner is introduced and tested in 100 map scenarios using a custom robotic simulation shell. The method combines a trap detection expert system, a low-level reflexive obstacle avoidance algorithm, and a trap evasion expert system, to achieve improved performance without sacrificing computational efficiency. Simulation results and evaluations are presented for the potential field, vector field, and HESV techniques. HESV's expert systems have been simplified to illustrate the performance improvements that result from a small amount of intelligence. Although recommendations for the structure of the path planning system are given, the purpose of the paper is to show the effectiveness of intelligent rules in path planning, rather than to define the actual rules to be used.

Paper Details

Date Published: 1 February 1994
PDF: 12 pages
Proc. SPIE 2058, Mobile Robots VIII, (1 February 1994); doi: 10.1117/12.167511
Show Author Affiliations
Markus A. Wolfensberger, Duke Univ. (United States)
Donald Wright, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 2058:
Mobile Robots VIII
William J. Wolfe; Wendell H. Chun, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?