对抗环境下多无人机轨迹规划与动态三维重建

Unmanned aerial vehicle (UAV) swarms have become a normalized element of modern warfare-as exemplified by the Russia-Ukraine conflict-serving as critical assets for strikes and reconnaissance. To satisfy the requirements of future maritime swarm operations, it is imperative to investigate dense-obstacle avoidance, cooperative bypass of non-cooperative targets, and three-dimensional reconstruction for UAV swarms operating in adversarial environments. To enhance autonomous perception and cooperative mapping in complex maritime scenarios, this work proposes an integrated approach for swarm intelligence planning and 3D reconstruction tailored to dynamic environments. Initially, in the cooperative trajectory planning stage, a leader-based UAV cooperative tracking method is proposed. The leader UAV is responsible for real-time locking and tracking of high-value noncooperative targets such as warships, while the follower UAVs maintain formation stability through a formationkeeping mechanism. Furthermore, when encountering mobile obstacles from other unmanned swarms, the swarm avoids threats through path re-planning and maneuvering actions, and quickly resumes target tracking after safely passing through. Ultimately, in the dynamic 3D reconstruction phase, after the UAV swarm approaches the target of interest, a multi-UAV cooperative circumnavigation and 3D reconstruction method is designed to achieve multiperspective observation and dynamic 3D reconstruction of non-cooperative maneuvering targets. Sea-based simulation experiments demonstrate that the methods proposed in this paper enable the UAV swarm to autonomously complete real-time tracking and efficient reconstruction of warships in complex adversarial environments, balancing mission completion rate and flight safety. This provides an effective solution for the reconnaissance, surveillance, and intelligence gathering tasks of UAV swarms in future battlefields.