Security Path Planning Based On A* Algorithm Framework

With the wide application of mobile robots in various fields,the autonomous navigation technology of mobile robots has become a hot research topic at home and abroad,and the path planning algorithm as the key technology of autonomous navigation has also become one of the focuses of researchers.This paper introduces various traditional path planning algorithms,analyzes the advantages and disadvantages of the traditional planning algorithm,leads to the problems existing in the traditional A* algorithm,and improves and merges the algorithm in the framework of A* algorithm,so that it has a variety of rich functions.In the traditional A* algorithm,the path node is too close to the obstacle,there are too many redundant nodes in the expansion process,and the search time of the algorithm is too long.Aiming at these problems,this paper proposes an improved hop search algorithm based on the optimization algorithm of A*algorithm,namely hop search algorithm.A new type of jump point is formed by combining the traditional jump point with the high risk jump point in the same corner of the obstacle.At the same time,the obstacle is puffed to keep a certain distance between the jump point and the obstacle,so as to improve the search range of each iteration of the algorithm.Finally,the non-direct subsequent hops are deleted to reduce the path length of the improved JPS algorithm and improve the performance of the algorithm.The simulation results show that the improved JPS algorithm increases the average search speed by 58.9%,reduces the average path length by 2.7%,and reduces the average collision risk by 41.3% in the complex environment.In order to enrich the function of the algorithm,it is integrated with the artificial potential field algorithm.By means of vector decomposition of gravitational potential field,a single gravitational potential field is decomposed into multiple gravitational component potential fields composed of new types of jumping points,each of which corresponds to a virtual subhead punctuation.Thepath oscillation problem in the traditional artificial potential field method is analyzed,and a more smooth path is obtained by using the dynamic obstacle scope method.By changing the gravity formula of the final target point,the gravity of the target is always greater than the repulsion force of the obstacle,and the problem of unreachable target is solved.Finally,the target tracking and dynamic obstacle avoidance of the fusion algorithm are realized by the strategy of position prediction and yaw Angle addition.The fusion algorithm is applied to multi-robot multi-objective programming and simulated on the warehouse map.In this paper,a task assignment method is proposed,which decomposes complex problems into simple linear programming problems by reducing the dimension and decomposing the multi-robot multi-objective problems with priority,so as to obtain the optimal solution based on the shortest total path length.The type of robot collision is analyzed and the local reaction mechanism of robot is established.Simulation on the class warehouse map verifies the effectiveness of the proposed method.