Experimental Test of Unmanned Ground Vehicle Delivering Goods Using RRT Path Planning Algorithm

This paper presents the experimental test of an unmanned ground vehicle delivering goods. Configuration and motion equations of the vehicle are illustrated, drivers for the vehicle motion control are introduced. In the presence of obstacles, the collision-free path connecting the vehicle from the start to the goal position is planned using Rapidly-exploring Random Tree (RRT) algorithm; collision detection, nodes selection, tree expansion, and path generation of the RRT are presented, the path optimization approach is discussed. To grip the goods, vehicle mechanical arms are manipulated based on the inversed kinematics, some control flow of the arms deployment for interacting with the vehicle motion control is applied. Experimental test of the vehicle delivering goods in face of static obstacles is presented; test result validates the applicability of the proposed framework.