A New Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

The paper thoroughly analyzes the shortcomings in the global path search process based on the traditional ACO algorithm. By integrating an improved ACO optimization approach with the A* algorithm, optimal paths can be efficiently generated for mobile robots navigating static environments. The enhanced ACO algorithm is capable of producing shorter paths with reduced turning points in a lesser number of iterations. Furthermore, a novel slope ACO algorithm is introduced to cater to more intricate terrains for optimal path exploration. The effectiveness of these two improved algorithms is validated through comparative simulations.