Abstract: Given that fruit fly optimization algorithm was restricted for falling into local optima easily, the smell concentration judge value S in fruit fly optimization algorithm was modified for dynamic path planning on lunar surface. The optimizing performance for path planning between the fruit fly optimization algorithm and the particle swarm optimization algorithm was compared through the simulations. Results show that the path planning based on the modified fruit fly optimization algorithm has better instantaneity and can not fall into local optima easily. Finally, an avoidance strategy was proposed for avoiding the unknown static obstacles that the lunar rover encounters in a dynamic environment.

Key words: Particleswarmoptimizationalgorithm, Localoptima, Fruitflyoptimizationalgorithm, Dynamicpathplanning, Lunarexploration