Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment,Key Lab of Industrial Computer Control Engineering of Hebei Province
National Key Research and Development Program of China,The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan),Hebei Youth Fund
Path planning technology is an important branch in the field of mobile robot research, which enables the robot to find a relatively optimal path safely and quickly in the multi obstacle environment. Aiming at the problems of blind search of ant colony algorithm, easy to fall into local optimization and slow convergence speed in global path planning, and DWA algorithm is difficult to effectively avoid dynamic obstacles in local path planning. A fusion algorithm of improved ant colony algorithm and DWA algorithm is proposed. Firstly, the initial path is constructed by adding the GRRT-Connect algorithm to unequal allocation of initial pheromones, so as to solve the local optimization problem caused by blind search in early planning in trap map. Secondly, the ant colony relay search method is added to solve the self deadlock problem of the ant tabu list. Thirdly, the slice optimization method is used to optimize the optimal path selection mechanism to obtain the global optimal path. Then, the DWA algorithm is run with the key points of the optimal path as the sub-target points, and an adaptive speed adjustment method is proposed for optimal driving. Finally, a pre-calculation method is proposed to avoid dynamic obstacles and achieve the effect of local planning. The simulation results show that compared with the results in the existing literature, The optimal path length of the fusion algorithm is shortened by 10.28% and the convergence speed is accelerated by 6.55%.