Robot Path Planning Method Combining Enhanced APF and Improved ACO Algorithm for Power Emergency Maintenance

Abstract

Considering the limited adaptability of the existing substation inspection robot path planning (PP) algorithms, the authors propose a novel PP method for mobile robots (MR) based on the structure of the ultra-high voltage (UHV) substation inspection robot system. The proposed method combines the improved ant colony optimization (IACO) algorithm and the enhanced artificial potential field (EAPF) algorithm. To minimize the interference of the pheromones, they introduced a pheromone adjustment coefficient in the later iterations of the algorithm. Furthermore, they improved the global pheromone update method, which is beneficial to the MR to search for the optimal path (OP) rapidly. They constructed two environmental models using the grid method, and they used MATLAB to implement comparative experiments between the proposed algorithm and other advanced methods. The results demonstrate that the proposed algorithm outperforms other methods in terms of running time, convergence speed, and global optimization ability.