An On-the-fly Evolutionary Algorithm for Robot Motion Planning

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 in generating a collisionfree path for a movable object among known and static obstacles. In this paper, we introduce a two stages evolutionary algorithm. The first stage is designed to compute a collission-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 environment dynamic modifications. Evolutionary techniques have shown 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 the Khepera simulator and a Lego Midstorms