Robot Path Planning Research Incorporating Improved A* Algorithm and DWA Algorithm
Keywords:Improved evaluation function; key point selection strategy; dynamic obstacles; trajectory optimization
For the traditional A* algorithm has problems such as long paths, large number of nodes, and the demand for dynamic obstacle cannot be avoided in complex environment. A mobile robot dynamic path avoidance method will be improved to improve the A * algorithm and improve DWA algorithm Two map environments are used for simulation verification. First, the evaluation function and key node selection strategy are optimized for the A* algorithm, and redundant nodes are deleted; then the dynamic obstacle distance evaluation function is added to the DWA algorithm which for the purpose of the obstacle avoidance performance can be enhanced. The results about the improved A* algorithm reduces 12.20% and 58.33% in path length and number of turning points respectively compared with the traditional A* algorithm can be obviously grasped by the simulation experiment; by using the fusion algorithm whose purpose of using arcs instead of the straight lines is to turn more smoothly, and can be closest to the global optimum while avoiding dynamic obstacles to complete the search.
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