Path Planning and Servo Tracking Control in Air-Ground Collaborative Unmanned System

Air-Ground collaborative unmanned systems face challenges in communication, autonomous navigation, motion planning, and servo tracking control. This paper focuses on the path planning and servo tracking problems of a designed Air-Ground collaborative unmanned system consisting of an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). A systematic function implementation framework is designed to realize the autonomous driving of the UGV in an unknown environment and servo tracking of the UAV to the UGV. The simultaneous localization and mapping (SLAM) technology is used to perform the mapping of the UGV. With map information, this paper introduces a path planner that satisfies the incomplete constraints and continuous state space of the UGV. Then, the UGV is controlled to track the planned path to a designated target given by the UAV. Considering two different application scenarios according to whether the position information can be obtained, two servo tracking controllers are proposed based on proportional differential (PD) and image-based visual servo (IBVS), respectively. Simulations are conducted to verify the feasibility and accuracy of the proposed approaches. The results show that the IBVS controller performs better than the PD controller in the system oscillation and reaction rate.