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The path planning of mobile robots is a critical technique for achieving robot autonomy. With the rapid development of the robot industry, the demand for mobile robot path planning is expanding. The primary algorithms involved in mobile robot path planning are summarized, along with their characteristics, in order to enhance mobile robot path planning and achieve effective obstacle avoidance and dynamic path planning. The A* algorithm and the artificial potential field approach are examined first, along with a summary of their drawbacks and an analysis of their underlying theories. Second, a new algorithm that combines the artificial potential field approach and the A* algorithm is summarized. The potential field function of the APF method is used to drive the search for the A* algorithm, and the enhanced algorithm is compared and examined based on path length, obstacle avoidance effect, and iteration times. In order to achieve the combination of global and local planning abilities, this algorithm uses the enhanced A* algorithm for global path planning and enhances the APF algorithm for local dynamic planning on the determined path. A comparative analysis was conducted using the simulation image. It offers other researchers a more thorough and effective path planning method for mobile robots. Lastly, the drawbacks of the A*APF fusion algorithm are highlighted, and recommendations for enhancement are made.
Junduo Liu (Tue,) studied this question.