多无人机协同追踪目标，避免碰撞与遮挡，实时规划轨迹。
DMVC-Tracker: Distributed Multi-Agent Trajectory Planning for Target Tracking Using Dynamic Buffered Voronoi and Inter-Visibility Cells
- 用动态缓冲沃罗诺伊区和可见性区域实现分布式轨迹规划。
- 在含数十障碍物环境中，每秒可生成数百条轨迹，响应时间毫秒级。
- 适合复杂场景下多无人机协同追踪任务，尤其适用于实时系统。
本文提出一种面向多智能体空中追踪的分布式轨迹规划方法。该方法利用动态缓冲沃罗诺伊单元（DBVC）和动态互可见单元（DIVC）构建分布式轨迹生成机制。其中，DBVC与DIVC为时变空间，可在避免智能体间碰撞与相互遮挡的同时，保持各智能体与运动目标的合适距离。将DBVC与DIVC结合基于伯恩斯坦多项式运动基元的高效追踪生成方法，相较此前工作更具鲁棒性且更少保守。算法在Intel i7台式机上可于数毫秒内完成单个智能体轨迹计算。在包含数十个障碍物的复杂场景中验证了其追踪性能。
原文摘要 · Abstract (English)
This letter presents a distributed trajectory planning method for multi-agent aerial tracking. The proposed method uses a Dynamic Buffered Voronoi Cell (DBVC) and a Dynamic Inter-Visibility Cell (DIVC) to formulate the distributed trajectory generation. Specifically, the DBVC and the DIVC are time-variant spaces that prevent mutual collisions and occlusions among agents, while enabling them to maintain suitable distances from the moving target. We combine the DBVC and the DIVC with an efficient Bernstein polynomial motion primitive-based tracking generation method, which has been refined into a less conservative approach than in our previous work. The proposed algorithm can compute each agent's trajectory within several milliseconds on an Intel i7 desktop. We validate the tracking performance in challenging scenarios, including environments with dozens of obstacles.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。