Chaotic Path Planner of Autonomous Mobile Robots Based on the Standard Map for Surveillance Missions

Abstract

This paper proposes a fusion iterations strategy based on the Standard map to generate a chaotic path planner of the mobile robot for surveillance missions. The distances of the chaotic trajectories between the adjacent iteration points which are produced by the Standard map are too large for the robot to track. So a fusion iterations strategy combined with the large region iterations and the small grids region iterations is designed to resolve the problem. The small region iterations perform the iterations of the Standard map in the divided small grids, respectively. It can reduce the adjacent distances by dividing the whole surveillance workspace into small grids. The large region iterations combine all the small grids region iterations into a whole, switch automatically among the small grids, and maintain the chaotic characteristics of the robot to guarantee the surveillance missions. Compared to simply using the Standard map in the whole workspace, the proposed strategy can decrease the adjacent distances according to the divided size of the small grids and is convenient for the robot to track.