Research On Optimization Of Mobile Robot Path Planning Algorithm

Mobile robot is a key scientific and technological research that the country vigorously develops,path planning has higher practical value and development prospects in the research of mobile robots,and has become a hot spot in various industries.As the path planning application environment is more complicated,various industries have higher requirements for path planning performance,and the optimization research of path planning algorithms has been put on the agenda.Therefore,in view of the path planning problem,this paper studies the optimization of the path planning algorithm of mobile robots.Firstly,research on the path planning algorithm,and clarify the direction of algorithm optimization.By studying the basic theories and development status of path planning algorithms,we realized the limitations of various algorithms,laid the foundation for algorithm optimization,and clarified the main direction of algorithm optimization.Secondly,research on the local path planning of mobile robot,and the optimization strategies for machine learning algorithms is proposed.In view of the problem of poor real-time obstacle avoidance performance of mobile robot in dynamic environment,a real-time obstacle avoidance decision model is established by using machine learning algorithm to improve the accuracy of real-time obstacle avoidance prediction.The simulation results verify the effectiveness of the local obstacle avoidance prediction performance of the machine learning algorithm.Then,research on the global path planning of the mobile robot,and the improved Smooth-Rapidly exploring Random Tree(S-RRT)algorithm is proposed.In view of the problem of long paths of mobile robots in static environments,the improved S-RRT algorithm is used to optimize the global path,improve the smoothness of the path and shorten the path length.The simulation results verify the flexibility and feasibility of the improved S-RRT algorithm.Finally,research on the global and local path planning of the mobile robot,and a genetic-ant colony hybrid optimization algorithm is proposed.In view of the problem of path planning in a complex environment,a hybrid of improved genetic algorithm and improved ant colony algorithm is adopted,which can obtain the global optimal path and avoid dynamic obstacles in real time.The simulation results verify the practicability and reliability of the genetic-ant colony hybrid optimization algorithm.