Adaptive Genetic Algorithms for Multi-Point Path Finding in Artificial Potential Fields

We present research work in progress into the use of adaptive genetic algorithms (AGAs) to search for collision-free paths in an artificial potential field (APF) representation of a cluttered robotic work-cell. We argue that the AGA approach promises to avoid the drawback of other APF approaches which are vulnerable to entrapment by local minima.