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Proceedings Paper

Robot trajectory planning using a genetic algorithm
Author(s): Daniel J. Pack; Gregory J. Toussaint; Randy L. Haupt
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Paper Abstract

In this paper, we studied the trajectory generation problem for a two-degrees-of-freedom robot in a workspace with obstacles. To generate the robot's trajectories, we developed a genetic algorithm to search for valid solutions in the configuration space. Our results present a novel perspective on the problem not seen in the conventional robot trajectory planners. The genetic algorithm approach is beneficial because it may be extended to plan trajectories for robots with more degrees of freedom. The evolutionary search process may allow the user to solve the trajectory problem in an n-dimensional space where the 'curse of dimensionality' inevitably stalls conventional methods. We demonstrate the algorithm with some examples and discuss the possible extension to higher order problems.

Paper Details

Date Published: 11 November 1996
PDF: 12 pages
Proc. SPIE 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments, (11 November 1996); doi: 10.1117/12.258129
Show Author Affiliations
Daniel J. Pack, U.S. Air Force Academy (United States)
Gregory J. Toussaint, U.S. Air Force Academy (United States)
Randy L. Haupt, U.S. Air Force Academy (United States)

Published in SPIE Proceedings Vol. 2824:
Adaptive Computing: Mathematical and Physical Methods for Complex Environments
H. John Caulfield; Su-Shing Chen, Editor(s)

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