A complete coverage path planning algorithm for mobile robot based on FSM and rolling window approach in unknown environment

Abstract

This paper presents an algorithm of complete coverage path planning (CCPP) for mobile robot in unknown environment based on the Finite State Machine (FSM) approach and rolling windows approach. The rolling window approach is used to detect the local environments. The robot only uses on-board sensors to acquire a limited range knowledge of the surroundings and construct the rolling windows. Then it translates the local unknown environment information to the known range. The proposed algorithm further abstracts the known environment as a union of robot-sized cells. In other words, range in rolling window is constructed to a cell map, or a grid map. Based on the grid map, the designed FSM method which has five states and three strategies is used to organize the CCPP task in the rolling windows. Strategies of the FSM method assume the greedy means to own the local optimal performance for the whole path planning task. To verify the designed method performance, we compare the simulation result with that of the method which uses random search planning. Simulation results show that the mobile robot can cover the entire workspace with low repetition rate and high work efficiency.