Path Planning of Intelligent Vehicle Based on Optimized A* Algorithm

Based on the traditional A* algorithm, this paper focuses on the shortcomings and disadvantage of the A* algorithm in process of the path search. Through the optimization of the ant colony algorithm, the search path of the improved A* algorithm is shorter, less time-consuming, smaller total turning angle, and the path is smoother. And then the comparison simulation is used to verify its correctness. Taking the intelligent vehicle as a hardware platform, sensors such as lidar and IMU carried are used to determine the pose of their own space and to acquire information on obstacles in the surrounding environment and establish an environmental map. Conduct indoor navigation experiments in real environment on the built hardware platform to verify its feasibility in practical application. The final experimental results show that in the indoor environment with obstacles, the car can accurately plan an optimal path, and can successfully avoid the obstacles and reach the target point, and the navigation is successful. This shows that the improved A* algorithm is not only theoretically effective, but also practically applicable