Rolling path planning of mobile robot based on automatic diffluence ant algorithm

This paper proposes a new method of robot path rolling planning based on automatic shunt ant algorithm. When a node is selected by multiple ants, later ants choose other paths to realize automatic shunting, thereby expanding the search range, enhancing the search diversity, and helping to obtain the optimal solution. The overall idea of the algorithm in this paper is to map the target point near the inner boundary of the robot's field of view, and use the new algorithm to plan the local optimal path of the robot, and the robot will move forward according to this local path. The robot repeats the process every time it advances, and reaches the end safely along a globally optimized path. Simulation experiments show that even in a complex unknown static environment, the algorithm in this paper can also be used to plan a global optimization path.