Path Optimization And Trajectory Tracking For Mobile Robots

The continuous innovation of science and technology supports the rapid development of society,and robot technology is one of the important technologies supporting the sustainable development of today’s society.Among them,how to improve the accuracy of robot navigation and positioning is an important research direction of robot technology,and the navigation and positioning technology of robot is closely related to the path optimization and trajectory tracking technology of mobile robot,which is inseparable.Therefore,the research on the path optimization and trajectory tracking of mobile robots is of great significance for the innovation and development of robot technology and the promotion of social progress.The paths planned by RRT(Rapid Exploring Random Tree)algorithm and A*algorithm have some problems,such as node redundancy,more turn times,uneven path and poor path quality.The Path optimization algorithm of diaphragm method with B-spline curve subdivision and the Path optimization algorithm of PTP(Path Turning Point)-B spline mobile robot were proposed to optimize the RRT Path and A*Path respectively.Finally,the mobile robot uses the linear time-varying model predictive control algorithm to track the optimized path.The main research contents are as follows:In order to solve the problem of RRT path,a path optimization algorithm based on diaphragm method and B-spline curve subdivision was proposed.First,the RRT algorithm was used to get the RRT path in the map.Then,the diaphragm method was used to determine the best caliber and extract the key signpost nodes under the best caliber through repeated experiments.Finally,the B-spline curve subdivision algorithm was used to smooth fit the extracted key signpost nodes.The effectiveness of the path optimization algorithm based on diaphragm method and B-spline curve subdivision is verified by comparing with RRT path simulation in different maps.By comparing with other path optimization algorithms in the same map,the superiority of path optimization algorithm based on diaphragm method and B-spline curve subdivision is verified.In order to improve the A*path,the PTP-B spline mobile robot path optimization algorithm was proposed.Firstly,the turning point of A*path is determined according to the angle change of A*path nodes.Secondly,the turning point of A*path is optimized according to the optimization rules and the optimized turning point of A*path is extracted as the initial node of PTP-B path.Then,the quasi-uniform B-spline function was used to fit the initial nodes of the PTP-B path to obtain the PTP-B primary optimization path,and the collision detection between the PTP-B primary optimization path and the obstacles in the map was carried out.Finally,nodes are added appropriately according to the collision detection results of the PTP-B primary optimal path.Then,the quasi-uniform B-spline function is used to generate the optimal PTP-B optimal path without collision with the obstacles in the map.Through the experiments in different environment maps and the comparison with the experimental data of A*path,it is effectively verified that the PTP-B spline mobile robot path optimization algorithm can significantly improve the A*path and improve the quality of A*path.Figure[33]Table[4]Reference[81]...