仿生算法协调运动：理论与实现
Biomimetic Algorithms for Coordinated Motion: Theory and Implementation
AI总结：
本文基于生物飞行行为，提出两种覆盖与聚群策略，通过轮式机器人与Vicon系统验证了运动伪装理论，并展示了基于局部信息的拓扑速度对齐方法，证明了生物启发在多智能体机器人系统中的应用价值。
摘要：
本文受生物飞行行为启发，如蜻蜓领地战斗和星鸦群体飞行，提出两种覆盖与聚群策略。利用先前关于相互运动伪装的理论研究，实现了适用于实验室测试平台的区域覆盖控制律，该平台配备轮式移动机器人和Vicon高速运动捕捉系统。同一测试平台还用于演示另一种基于局部信息的策略，称为拓扑速度对齐，使智能体朝同一方向移动。本文展示了生物启发在多智能体机器人集体设计中的适用性。
英文摘要：
Drawing inspiration from flight behavior in biological settings (e.g. territorial battles in dragonflies, and flocking in starlings), this paper demonstrates two strategies for coverage and flocking. Using earlier theoretical studies on mutual motion camouflage, an appropriate steering control law for area coverage has been implemented in a laboratory test-bed equipped with wheeled mobile robots and a Vicon high speed motion capture system. The same test-bed is also used to demonstrate another strategy (based on local information), termed topological velocity alignment, which serves to make agents move in the same direction. The present work illustrates the applicability of biological inspiration in the design of multi-agent robotic collectives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
