Using genetic algorithms for robot motion planning

We present an ongoing research work on robot motion planning using genetic algorithms. Our goal is to use this technique to build fast motion planners for robot with six or more degree of freedom. After a short review of the existing methods, we will introduce the genetic algorithms by showing how they can be used to solve the invers kinematic problem. In the second part of the paper, we show that the path planning problem can be expressed as an optimization problem and thus solved with a genetic algorithm. We illustrate the approach by building a path planner for a planar arm with two degree of freedom, then we demonstrate the validity of the method by planning paths for an holonomic mobile robot. Finally we describe an implementation of the selected genetic algorithm on a massively parallel machine and show that fast planning response is made possible by using this approach.

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Source European Conference on Artificial Intelligence (ECAI92), Wien (Austria)
Author Ahuactzin, Juan-Manuel, Talbi, El-Ghazali, Bessiere, Pierre, Mazer, Emmanuel
Maintainer CCSD
Last Updated May 21, 2026, 00:01 (UTC)
Created May 21, 2026, 00:01 (UTC)
Identifier hal-00069064
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire d'Informatique Fondamentale et d'Intelligence Artificielle (LIFIA) ; Institut National Polytechnique de Grenoble (INPG)
creator Ahuactzin, Juan-Manuel
date 1992-05-21T00:00:00
harvest_object_id 9a9d0f3d-db17-427a-983d-2ad883ea0389
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-09-27T00:00:00
set_spec type:COMM