Infra-Swarm：通过近红外光谱视觉实现基于视觉的鲁棒多机器人集群
Infra-Swarm: Robust Vision-Based Multi-Robot Swarming via Near-Infrared Spectral Vision
- Westlake University（西湖大学）
- The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
- Zhejiang University（浙江大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究针对分布式集群受带宽或环境限制问题，提出Infra-Swarm，通过机器人配备近红外光源和相机，利用光学耀斑测量邻居3D位置，借助窄带滤波器抗干扰，以最小计算开销实现集群大规模可扩展性。
AI中文摘要：
分布式集群通常依赖主动无线通信或被动视觉，常受带宽限制或环境敏感性阻碍。本文提出Infra-Swarm，一种基于视觉的鲁棒集群。每个机器人配备近红外光源和四个普通灰度相机。该系统基于捕获图像中光学耀斑的位置（方位）和强度（亮度）直接测量邻居的厘米级三维位置。利用940nm窄带滤波器物理排除99.2%的环境光干扰，感知前端实现了针对光照变化的硬件级鲁棒性。此外，其最小计算开销为资源受限硬件上机器人集群的大规模可扩展性提供了弹性基础。
英文摘要：
Distributed swarms typically rely on either active wireless communication or passive vision, and they are frequently hindered by bandwidth constraints or environmental sensitivity. This paper proposes Infra-Swarm, a robust vision-based swarm. Each robot is equipped with a near-infrared light source and four ordinary gray-scale cameras. The Infra-Swarm system directly measures the centimeter-level 3D position of neighbors based on the position (bearing) and intensity (strength) of optical flares in the captured images. By utilizing 940 nm narrow-band filters to physically reject 99.2% of ambient light interference, the perception front-end achieves hardware-level robustness against illumination variations. Furthermore, its minimal computational overhead provides a resilient foundation for the massive scalability of robotic collectives on resource-constrained hardware.
