An Improved A-star Algorithm for Path Planning Based on Ant Colony Optimization

Mobile robots are widely used in industrial manufacturing, agricultural production, health care, home services, transportation, and other fields. As the most basic and important research topic in the field of mobile robots, path planning technology has always been the focus of attention. To solve the problems caused by the traditional A* algorithm that the path length is too long and the trajectory is not smooth, This paper proposes an improved A* algorithm based on Ant Colony Optimization. Firstly, use the A* algorithm to roughly find a constrained shortest path. Secondly, extract the key nodes of the shortest path and calculate the distribution of obstacles between these key nodes. Finally, use the improved ant colony algorithm to optimize the searched path to generate the final path. Simulation experiments show that the time complexity and space complexity of the improved A* algorithm are reasonable. The generated path length is shorter, the total turning angle is smaller, the trajectory is smoother, and it is more suitable for the real environment. Compared with the traditional A* algorithm, it has obvious advantages.