Multi-Robot Full Coverage Algorithm Considering Charging Pile Constraints

To address the challenges of low efficiency and limited dynamic planning capabilities in multi-robot battery replacement tasks within unknown environments, we propose a charging scheduling algorithm that incorporates a graded charging threshold (GCT) function for enhanced multi-robot path planning. Initially, a raster map is employed to represent the operational area, and the region is covered using a full coverage algorithm that combines an obstacle-guided approach with a start point and backtracking mechanism (OSPGB). Next, the GCT function is integrated for optimization, enabling the robot to determine the optimal time for battery replacement. This approach helps prevent power loss and minimizes longer charging routes during the coverage process. Ultimately, simulation experiments are conducted across various environments, demonstrating that the proposed algorithm significantly outperforms the OSPGB algorithm in terms of the number of turns and path uniformity. Specifically, the number of turns is reduced by 7.8%, and the optimization rate for path uniformity reaches 94.2%.