Decentralized state estimation is one of the most fundamental components of autonomous aerial swarm systems in GPS-denied areas yet it still remains a highly challenging research topic. Omni-swarm, a decentralized omnidirectional visual-inertial-UWB state estimation system for aerial swarms, is proposed in this paper to address this research niche. To solve the issues of observability, complicated initialization, insufficient accuracy, and lack of global consistency, we introduce an omnidirectional perception front-end in Omni-swarm. It consists of stereo wide-FoV cameras and ultra-wideband sensors, visual-inertial odometry, multi-drone map-based localization, and visual drone tracking algorithms. The measurements from the front-end are fused with graph-based optimization in the back-end. The proposed method achieves centimeter-level relative state estimation accuracy while guaranteeing global consistency in the aerial swarm, as evidenced by the experimental results. Moreover, supported by Omni-swarm, inter-drone collision avoidance can be accomplished without any external devices, demonstrating the potential of Omni-swarm as the foundation of autonomous aerial swarms.

翻译：分散的状态估计是全球定位系统封闭区自主空中群集系统的最根本组成部分之一,但它仍然是一个极具挑战性的研究课题。Omni-swarm,一个分散的空中群集全向直观-内皮-UWB国家估计系统,在本文中建议用于解决这一研究领域。为解决可观察性、复杂初始化、不够准确性和缺乏全球一致性等问题,我们在Omni-swarm引入一个全向感知前端。它包括立体宽频视频摄像头和超广频传感器、视觉非光伏测、多轨道地图本地化和视觉无人机跟踪算法。前端的测量与后端的基于图形的优化相结合。拟议方法达到厘米相对状态估计准确性,同时保证空中群的全球一致性,正如实验结果所证明的那样。此外,在Omni-swarm的支持下,可以在没有外部装置的情况下实现跨轨道碰撞的避免,从而展示了Omni的自主空中基础。