Research on path planning in obstacle avoidance control of mobile robot

In order to improve the obstacle avoidance ability of mobile robot in complex dynamic environment and enable it to complete the obstacle avoidance task safely and efficiently under the guidance of global path, it is very important to plan a reasonable global path before moving. In view of the low optimization accuracy and convergence of traditional genetic algorithm in the process of path planning, the fitness function was designed to improve the genetic algorithm, and the research method of intelligent fusion of whale optimization algorithm and genetic algorithm was proposed to improve the optimization of the optimal operator in the genetic algorithm, effectively reduce the workload required by the operation iteration, and improve the accuracy and efficiency of conventional genetic algorithm in global path planning.