Research On Robot Dynamic Path Planning Based On Improved A~* Potential Field Method

With the continuous maturity of mobile robot application technology,it is more and more widely used in people's daily life and production,but at the same time,it also has higher requirements for all aspects of robot performance.As one of the key technologies of robot research,path planning has a direct impact on the safety and effectiveness of robot work.This paper studies the dynamic path planning of indoor mobile robot in the environment of unknown moving obstacles,and proposes an improved fusion algorithm of A~* algorithm and artificial potential field method,which solves the problems of path vibration and inability to deal with dynamic obstacles in potential field method,and realizes the global path optimization.Finally,the experiment platform is designed to verify the dynamic path planning algorithm.The specific work is as follows:1.In view of the low utilization of time and space caused by the large amount of calculation in the process of A~* algorithm's path finding,and the problem of many turning points in the path planning,a search method of node deletion is proposed.By preprocessing the traditional A~* algorithm,the appropriate hop points are selected to delete the unnecessary nodes,the access time to the total nodes is reduced by about 42.45%,and the search time of A~* algorithm is improved The quality of the path is optimized by visual point detection,which makes the path more smooth and natural.2.An improved algorithm with relative position and relative velocity is proposed,which can reduce the repulsion field in real time when the robot approaches the target,avoid the unavailability of the target point caused by the local extreme value,and avoid collision in real time based on the relative speed of the moving obstacles,which improves the lack of real-time performance of the traditional artificial potential field method and the vulnerabilityto fall into the local extreme value Sink.Compared with the traditional potential field method,the improved potential field algorithm reduces the path length by 11.1% and the running time by 12.9%.3.The improved A~* algorithm and the improved potential field method are integrated.First,the improved A~* algorithm is used for global optimal path planning by simulating the human route finding logic.When the mobile robot enters the dynamic obstacle influence range,the improved potential field method is transformed for real-time dynamic obstacle avoidance.At the same time,the path planned by A~* algorithm is used as the dynamic target for real-time tracking to complete the global path planning.The feasibility of the algorithm is verified by simulation,which can effectively reduce the total length of the path,reduce the cumulative angle and improve the quality of the path.4.Analyze the hardware requirements of dynamic path planning experiment,design and build a wheeled mobile car with STM32 as the main control board,select laser ranging sensor as the environmental sensor,and convert the environmental information into coordinate information.The experimental results show that the algorithm is effective and reliable.