Computation of a collision-free path for a movable object among obstacles is an important problem in the fields of robotics. The simplest version of motion planning consists of generating a collision-free path for a movable object among known and static obstacles. In this paper, we introduce a two stage evolutionary algorithm. The first stage is designed to compute a collision-free path in a known environment. The second stage is designed to make on-the-fly updates of the robot current path according to the dynamic environmental modifications. Evolutionary techniques have proven to be useful to both quickly compute a new path and to take advantage of the initial path from the first stage. The tests have been made using simulations and a Lego Mindstorrns Robot. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Alfaro, T., & Riff, M. C. (2005). An on-the-fly evolutionary algorithm for robot motion planning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3637 LNCS, pp. 119–130). https://doi.org/10.1007/11549703_12
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