Multiple robot motion planning on A* and RRT* algorithm

Abstract

Abstract In recent years, multi-robot systems have been widely used in different fields. In order to ensure that each robot in the system can reach the target point and complete the task correctly, the path planning of the multi-robot system is significant. The path planning of the multi-robot system can effectively ensure that the robot selects the appropriate target and completes the task, and during the planning, it can ensure that the task completion time of the total system is the shortest or the total cost is the lowest. Experiments are carried out without considering the kinematics and physical properties of the robot itself, and it is assumed that each robot can accurately know its own position information. In this paper, we propose an A* algorithm for target trajectory planning that integrates multiple trajectories and minimizes running costs by task assignment through a linear programming model. At the same time, by adjusting the planning method of the estimated cost, the error caused by the difference between the nonlinear path and the straight line distance is reduced. After experiments, the effectiveness of the linear programming model and the difference in computation time and running time between A* and RRT* algorithms are demonstrated. What’s more, A* outperforms RRT* in completion time, while RRT* has a shorter computation time.