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Hybrid Path Planning Of Mobile Robot Based On Improved A~* Algorithm And Artificial Potential Field Method

Posted on:2024-09-08Degree:MasterType:Thesis
Country:ChinaCandidate:H LiuFull Text:PDF
GTID:2568307151959549Subject:Control Science and Engineering
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With the rapid development of new generation of information technology such as artificial intelligence and Internet of things,mobile robot technology presents many new characteristics and its application fields are becoming more and more extensive.Mobile robots can be used in intelligent manufacturing,logistics transportation under complex working conditions and autonomous path planning and navigation in outdoor environment,which has a wide range of application prospects.The autonomous path planning technology of mobile robot is the key technology of autonomous driving and obstacle avoidance,and also one of the core technologies for mobile robot to be widely used.In this paper,mobile robot is taken as the research object,and problems such as poor realtime performance and weak dynamic obstacle avoidance ability exist in mobile robot path planning are studied.The main research contents are as follows:Firstly,aiming at the problems of A~* algorithm for global path planning,such as the number of traversal nodes,low search efficiency,many turning points and large turning angles,A~* algorithm based on bidirectional jump-point search is proposed.To reduce the number of traversal nodes and improve the search efficiency,the bidirectional hop search method is adopted.Redundancy point elimination mechanism is designed to eliminate redundant nodes and unnecessary inflection points on the path to reduce the number of turning points and shorten the length of the path.Finally,the path is smoothed by three Bspline curves to reduce the turning Angle.Simulation results show that the proposed bidirectional jump-point search based on A~* algorithm has higher planning efficiency,and can solve the traditional A~* algorithm search efficiency is low,the path is not smooth and other problems.Secondly,aiming at the problem of unreachable target point and local minimum value of artificial potential field method used in local path planning,an improved artificial potential field method based on fusion simulated annealing algorithm is proposed.By setting the local radiation range for the target point and setting the gravitational gain coefficient in stages,the gravitational force of the robot is greater than the repulsive force when there are obstacles near the target point,so as to solve the unreachable problem of the target point.When the robot falls into the local minimum,the simulated annealing method is used to set a random target point and guide the robot to move in the direction where the total potential field decreases until it escapes from the local minimum area.The simulation results show that the proposed fusion simulated annealing algorithm can solve the problem of unreachable target points and local minimum,and the planning efficiency is higher than that of the artificial potential field method,and the total turning Angle of the path is smaller.Finally,aiming at the path planning problem of mobile robots in dynamic environment with unknown obstacles and dynamic obstacles,A hybrid path planning algorithm based on A~* algorithm and artificial potential field method is proposed.A~*algorithm based on bidirectional jump search was used to obtain the global path,and the dynamic tangential method was used to smooth the path,and then the turning point was set as the global subpoint.Then,the improved artificial potential field method is called in segments for local path planning to complete the obstacle avoidance of dynamic and unknown obstacles and improve the dynamic obstacle avoidance ability of the mobile robot in the dynamic environment.Simulation results show that the proposed hybrid path planning algorithm based on A~* algorithm and artificial potential field method can effectively avoid unknown obstacles and dynamic obstacles in dynamic environment,and can return to the global optimal path after local obstacle avoidance,and complete the path planning task.
Keywords/Search Tags:mobile robot, path planning, A~* algorithm, artificial potential field method, dynamic obstacle avoidance
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