Research On Path Planning Algorithm Based On A* Algorithm

Robot technology is an intelligent industry representative technology that constantly integrates information technology and industrialization.It is an important symbol of scientific and technological innovation at present.Path planning,as a research hotspot in robotics technology,has been attracted to quite a few researchers.The heuristic search algorithm A* algorithm is widely used to solve the path planning problem due to its advantages of simplicity,high efficiency,high operability,and high accuracy.Nevertheless,the A* algorithm is influenced by its heuristic function and node search strategy.As a result,the planning path in many environments is not the optimal path,and the inflection point on the path is too much.Moreover,when the environment information is too complex,the algorithm search becomes inefficient,and the A* algorithm is unsuitable for solving the problem of path planning in the presence of a dynamic obstacle environment.In this paper,the above defects of A* algorithm are mainly studied in the following aspects:(1)Based on the idea of grid method to realize the environment modeling and expand the known environmental information,robot is regarded as the preprocessing method of the environmental information of its centroid location particle;and establish the environment model without grid lines and optimize the grid grid coordinates representation method.(2)In order to improve the disadvantages of the A* algorithm that the planning path is not optimal and the efficiency of the algorithm is reduced when the environment map is magnify and complicated,a comprehensive improvement of the A* algorithm is proposed to extend the algorithm to search the neighborhood range and use the least binary heap to optimize the A* algorithm.Simulation experiments verify that the synthetic improved A* algorithm is shorter than the original algorithm's optimal path length,and effectively improves the global search efficiency of the algorithm.(3)In order to improve the ability of A* algorithm to address dynamic environment path planning problems,introducing the ant colony algorithm thought,proposed an A* ant colony algorithm combining global and local path pheromone update method and A* algorithm heuristic function traversal idea.The results show that the A* ant colony algorithm has a shorter optimal path distance and improves the convergence efficiency of the ant colony algorithm.The simulation results on the dynamic obstacle environment also show that the A* ant colony algorithm address the problem of path planning with dynamic obstacles has good adaptability and robustness.(4)The post-processing stage of the path planning combines the cubic uniform B-spline function transition process to improve the planning path algorithm and optimize the B-spline function by reducing the control vertices.The simulation experiment verifies that the B-spline function eliminates the improved algorithm at the optimal path turning point path spiking is feasible and effective.