The A* algorithm is a heuristic search algorithm widely used in the fields of path planning and graph search. This paper aims to delve deeply into the principles, implementation, and performance optimization of the A* algorithm in practical applications. Firstly, we elaborate on the basic principles of the A* algorithm, including the definitions of cost function and heuristic function, as well as how to achieve efficient search by maintaining open lists and closed lists. Secondly, we analyze the application of the A* algorithm in path planning problems. By constructing environmental models and designing appropriate heuristic functions, we achieve optimal path search from the start point to the end point. Additionally, we explore the performance optimization methods of the A* algorithm, including strategies such as utilizing priority queues to manage nodes to be searched and dynamically adjusting heuristic functions, to improve the execution efficiency and search accuracy of the algorithm. Finally, through a series of experiments and case studies, we verify the effectiveness and superiority of the A* algorithm in path planning problems. The research results of this paper provide beneficial references and insights for the application of the A* algorithm in related fields.