Mission Planning for Surrounding Target Tracking of USV Based on Behavior Tree in Multi-Obstacle Environment

Unmanned Surface Vehicle (USV), has become an essential tool in various applications such as surface surveillance, environmental monitoring and maritime military. Nevertheless, autonomous and effective mission execution in complex and dynamic marine environments through USV remains a significant challenge. Particularly in tailored missions, reliance solely on path planning and control is insufficient to endow USV with robust autonomy. In this paper, we introduce a surrounding target tracking mission planning method for USV based on the behavior tree (BT) model. Firstly, two guidance laws are proposed for surrounding target tracking and obstacle avoidance using Guiding Vector Field (GVF) algorithm, respectively. Secondly, the BT model effectively manages and executes the generation and superposition of GVF, and USV is driven to fulfill its intended mission autonomously. Simulations are conducted with a USV tracking a moving target while avoiding obstacles, and the experimental results demonstrate that the USV can safely and autonomously complete the target tracking mission using the proposed method.