Abstract
In this paper, an improved cockroach swarm optimization, called cockroach swarm optimization with expansion gird (CSO-EG), is presented and applied to motion planning of autonomous mobile robot. In CSO-EG, the expansion gird method is used to model workspace. By computing the weight factor, the Euclidean distance from each candidate to the destination cell and the pheromone strength of each candidate cell are use as the heuristic information together. For increasing the variety of path, a random choosing cell strategy is introduced. The simulation experiments demonstrate that the CSO-EG algorithm can quickly get the optimal or near-optimal path in a workspace populated with obstacles.
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