Multi-UAV Adaptive Path Planning in Complex Environment Based on Behavior Tree

Abstract

In this paper, we consider a scenario where multiple tracking unmanned aerial vehicles (UAVs) pursue a target UAV in a complex environment. Consider the fast airspeed of the UAV, the path planning needs to be finished in a limited time. Moreover, the complex environment may involve diverse geographical areas, which raises the challenges for the path planning algorithms. For the first challenge, we will adopt the real-time algorithms to keep the efficiency of path planning. For the challenge of environment diversity, we involve the behavior tree (BT) model and propose a BT-organized path planning (BT-OPP) method aiming at achieving adaptive scheduling of different path planning algorithms in different geographical areas. Furthermore, in order to take the advantages of multiple tracking UAVs, we propose a virtual-target-based tracking (VTB-T) method which can make the tracking UAVs pursue the target UAV collaboratively. The effectiveness of the proposed BT-OPP method and the VTB-T method are verified by analysis and numerical results for different system configurations, showing that a substantial target tracking efficiency improvement may be achieved in comparison with the benchmark.