Abstract:In order to overcome the shortcomings of slow search efficiency and low optimization precision of traditional intelligent algorithms in solving path planning problems of mobile robots under complex environment,an improved sooty tern optimization algorithm (ISTOA) was proposed.Based on STOA algorithm,Circle chaotic mapping mechanism was introduced to ensure the quality of the initial population and improve the initial search efficiency of the algorithm.At the same time,the rotary somersault search strategy was proposed to update the feeding position of the algorithm,by which the local optimization ability of the algorithm was improved.During the migration,the combination of sinusoidal control non-collision factor and adaptive Lévy flight strategy was introduced to balance the global search and local search of the algorithm.The effectiveness of the ISTOA algorithm was verified by three different cases in path planning of mobile robot.The results show that the ISTOA algorithm can be used to obtain the global optimal path quickly and stably,and the overall optimization ability is better than other algorithms,by which the optimal path planning problem of mobile robot in complex environment is solved effectively.