Autonomous aerial tracking with drones offers vast potential for surveillance, cinematography, and industrial inspection applications. While single-drone tracking systems have been extensively studied, swarm-based target tracking remains underexplored, despite its unique advantages of distributed perception, fault-tolerant redundancy, and multidirectional target coverage. To bridge this gap, we propose a novel decentralized LiDAR-based swarm tracking framework that enables visibility-aware, cooperative target tracking in complex environments, while fully harnessing the unique capabilities of swarm systems. To address visibility, we introduce a novel Spherical Signed Distance Field (SSDF)-based metric for 3-D environmental occlusion representation, coupled with an efficient algorithm that enables real-time onboard SSDF updating. A general Field-of-View (FOV) alignment cost supporting heterogeneous LiDAR configurations is proposed for consistent target observation. Swarm coordination is enhanced through cooperative costs that enforce inter-robot safe clearance, prevent mutual occlusions, and notably facilitate 3-D multidirectional target encirclement via a novel electrostatic-potential-inspired distribution metric. These innovations are integrated into a hierarchical planner, combining a kinodynamic front-end searcher with a spatiotemporal $SE(3)$ back-end optimizer to generate collision-free, visibility-optimized trajectories.Deployed on heterogeneous LiDAR swarms, our fully decentralized implementation features collaborative perception, distributed planning, and dynamic swarm reconfigurability. Validated through rigorous real-world experiments in cluttered outdoor environments, the proposed system demonstrates robust cooperative tracking of agile targets (drones, humans) while achieving superior visibility maintenance.

翻译：无人机自主空中追踪在监控、影视拍摄与工业巡检领域具有广阔应用前景。尽管单无人机追踪系统已得到广泛研究，但基于集群的目标追踪仍探索不足，尽管其具备分布式感知、容错冗余与多方向目标覆盖的独特优势。为填补这一空白，我们提出了一种新型去中心化LiDAR集群追踪框架，能够在复杂环境中实现可见性感知的协同目标追踪，并充分发挥集群系统的独特能力。针对可见性问题，我们引入了一种基于球面符号距离场的新型三维环境遮挡表征度量，并结合一种支持实时机载SSDF更新的高效算法。提出了一种支持异构LiDAR配置的通用视场对准代价函数，以确保目标观测的一致性。通过协同代价函数增强集群协调性，该函数可维持机器人间安全间距、避免相互遮挡，并借助一种新型静电势启发式分布度量显著促进三维多方向目标包围。这些创新被集成至分层规划器中，结合运动学前端搜索器与时空$SE(3)$后端优化器，生成无碰撞且可见性最优的轨迹。本系统部署于异构LiDAR集群，其完全去中心化实现具备协同感知、分布式规划与动态集群重构能力。通过在杂乱户外环境中的严格实景实验验证，所提系统在保持卓越可见性的同时，实现了对敏捷目标（无人机、人体）的鲁棒协同追踪。