Aiming at the path planning problem of mobile robot passing through multiple target points with the shortest path under two-dimensional raster map, this paper proposes a method combining an improved A* algorithm with an annealing genetic algorithm. For the problem that A* algorithm will search adjacent nodes in turn, Jump Point Search (JPS) algorithm is introduced to avoid the search of surrounding nodes by searching the jump point of the current node and reduce the calculation time. In view of the prematurity problem of genetic algorithm, the simulated annealing algorithm is introduced to make the simulated annealing algorithm and genetic algorithm complement each other and overcome the prematurity problem of genetic algorithm effectively. By using TSPLIB dataset, the path planning of the improved genetic algorithm is obviously better than that of the original genetic algorithm. Finally, the feasibility and effectiveness of the method are verified by simulation, and the shortest safe path can be found quickly in the process of optimization.

Zeping Yang, Xiangguo Sun. A new multi-objective point path planning algorithm for mobile robots. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 2: 28-35. https://doi.org/10.25236/AJCIS.2023.060205.

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