A Hybrid Path-Planning Algorithm Combining the Improved A-Star Algorithm with the DWA

To address the limitations of the traditional A-star algorithm, such as long search times, excessive redundant nodes, numerous turning points, and an inability to handle dynamic obstacles, this paper proposes a hybrid path planning method that integrates an improved A-star algorithm with the Dynamic Window Approach. First, a grid-based map is constructed for environment modeling, and an obstacle inflation strategy is employed to enhance path safety. On this basis, the traditional A-star algorithm is enhanced by introducing fixed reference points to guide the search direction, thereby reducing unnecessary node expansions and improving search efficiency. Subsequently, redundant nodes are eliminated using a triangle pruning strategy, and the combination of the triangle inequality and the bisection method is applied for further node optimization. The path is then smoothed using a dynamic circular arc-cutting method. Finally, the DWA algorithm is incorporated for real-time local path adjustments to handle dynamic obstacles, ensuring the continuity and collision-free nature of the global path. Simulation and real-world experimental results demonstrate that the proposed hybrid path planning method outperforms the traditional A-star algorithm in terms of path length, planning time, and path smoothness. It effectively meets the requirements of dynamic obstacle avoidance in complex environments and holds significant potential for practical applications.