无需通信的无人机群在林冠下避障集群飞行，误差可控。
Distributed Lloyd-Based algorithm for uncertainty-aware multi-robot under-canopy flocking
- 基于分布式洛伊德算法实现无通信集群
- 保证飞行中不碰撞障碍物与其它无人机
- 适合林区等复杂环境的多机协同任务
本文提出一种分布式算法，实现复杂环境下无人机在恒定高度飞行的集群行为，无需显式通信、无需环境先验信息，仅依赖机载感知与计算。给出了确保避障且不超出预设邻居距离（集群或邻近维持约束）的充分条件。该方法能有效处理追踪误差与机载传感误差，在密集场景下运行稳定。通过不同数量无人机的仿真及真实森林环境中最多四架无人机的实验验证了算法有效性。
原文摘要 · Abstract (English)
In this letter, we present a distributed algorithm for flocking in complex environments that operates at constant altitude, without explicit communication, no a priori information about the environment, and by using only on-board sensing and computation capabilities. We provide sufficient conditions to guarantee collision avoidance with obstacles and other robots without exceeding a desired maximum distance from a predefined set of neighbors (flocking or proximity maintenance constraint) during the mission. The proposed approach allows to operate in crowded scenarios and to explicitly deal with tracking errors and on-board sensing errors. The algorithm was verified through simulations with varying number of UAVs and also through numerous real-world experiments in a dense forest involving up to four UAVs.
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。