Multi-objective path planning for mobile robot based on ACO -APF fusion algorithm - Zhao, Lin; Qiao, Yanhua; Feng, Fang (SPIE, 2023)
Path planning of mobile robot is an important research direction of mobile robot, there are some defects in the path planned by the traditional Ant Colony Optimization (ACO) algorithm, many turning points appear in the planned path, some points in the planned path are very closed to the obstacles, all of these increase the probability that the mobile robot will hit an obstacle. Although the path planned by the Artificial Potential Field (APF) algorithm is relatively smooth, it often has redundant segments, and at the same time, it is not necessarily the optimal path. In order to solve these problems, ACO -APF fusion algorithm is proposed in this paper. The path planned by the ACO -APF fusion algorithm can keep a safe distance from the obstacles and have fewer turning points. To verify the performance of the fusion algorithm, the path smoothing performance and the select performance are tested. The ACO -APF fusion algorithm can also be used for multi-objective point path planning. In the simulation test, the grid map of the hospital scene is created, by inputting the starting point and different target points in the algorithm, a path containing four target points is planned. Simulation results show that ACO -APF fusion algorithm can plan out multi-objective point path according to user requirements.