Chaotic Path Planning for Mobile Robots Based on the Chen System

Coverage path planning is an algorithm that generates efficient robot trajectories to ensure complete coverage of a designated area. It is widely used in applications such as cleaning, surveillance, and exploration of unknown environments. The chaotic mobile robot, driven by a controller with chaotic dynamics, ensures full workspace coverage without a map or a global motion plan. In this paper, different variables of the Chen system and the Lorenz system are used to generate the chaotic motion of the robot. By comparing the trajectory coverage rate of the three variables [Formula: see text] in the Chen system under the same initial conditions and running time, it is found that the third variable z of the Chen system performs the best in bounded workspace and is better than those in the Lorenz system. Furthermore, in order to illustrate the advantages of chaotic path planning, we consider several more complex robot workspaces: the case of a bounded workspace with obstacles and the case of various nonconvex bounded workspaces. The simulation results show that the robot trajectory corresponding to the z-variable of the Chen system not only maintains the highest coverage rate but also can successfully pass through narrow channels in nonconvex areas for comprehensive retrieval. Finally, the relationship between the qualitative properties of the two chaotic systems and the coverage rate of the chaotic robot’s trajectory is discussed in detail.