A path planning algorithm based on the fusion of the improved A*algorithm and the random obstacle avoidance dynamic window method(ROA-DWA)was proposed in order to address the issues of excessive traversal nodes,redundant points,non-smooth paths,lack of global guidance,susceptibility to local optima,and low safety in traditional A*algorithm and dynamic window approach(DWA)for robot path planning.The search efficiency was improved by adjusting the weights of heuristic functions,Floyd's algorithm,redundant point deletion strategy,static and dynamic obstacle classification,and speed adaptive factor.The length of the path and the number of inflection points were reduced,and the influence of known obstacles on the path was minimized to improve the efficiency of dynamic obstacle avoidance,which enabled the robot to smoothly arrive at the target point and improved the safety of the robot,and better adapted to complex dynamic and static environments.The experimental results show that the algorithm has better global optimality and local obstacle avoidance ability,and shows better advantages in large maps.
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