The decentralized state estimation is one of the most fundamental components for autonomous aerial swarm systems in GPS-denied areas, which still remains a highly challenging research topic. To address this research niche, the Omni-swarm, a decentralized omnidirectional visual-inertial-UWB state estimation system for the aerial swarm is proposed in this paper. In order to solve the issues of observability, complicated initialization, insufficient accuracy and lack of global consistency, we introduce an omnidirectional perception system as the front-end of the Omni-swarm, consisting of omnidirectional sensors, which includes stereo fisheye cameras and ultra-wideband (UWB) sensors, and algorithms, which includes fisheye visual inertial odometry (VIO), multi-drone map-based localization and visual object detector. A graph-based optimization and forward propagation working as the back-end of the \textit{Omni-swarm} to fuse the measurements from the front-end. According to the experiment result, the proposed decentralized state estimation method on the swarm system achieves centimeter-level relative state estimation accuracy while ensuring global consistency. Moreover, supported by the Omni-swarm, inter-drone collision avoidance can be accomplished in a whole decentralized scheme without any external device, demonstrating the potential of Omni-swarm to be the foundation of autonomous aerial swarm flights in different scenarios.
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,它仍然是一个极具挑战性的研究课题。为了解决这一研究重点,本文建议建立一个分散的全向视觉-内皮-世界发展组织(UWB)国家评估系统,用于空中群集。为了解决可观察性、复杂初始化、不够准确性和缺乏全球一致性等问题,我们引入了全向式感知系统,作为Omni-swarm的前端,由全向式传感器组成,其中包括立体鱼眼照相机和超广频传感器,以及算法,其中包括鱼眼视觉惯性奥多度测量仪(VIO)、多轨道地图本地化和视觉物体探测器。基于图的优化和前向传播作为hextit{Omni-swarm}的后端,我们引入一个全向式感知系统,以整合从前端的不同测量。根据实验结果,拟议的分散式状态估算方法包括立体鱼视像摄像机和超广频带传感器(UWB)传感器(UWB)传感器,以及算法,包括鱼眼视视惯惯性惯性惯性惯性惯性惯性惯性惯性惯性局部直径系统,同时实现整个的直径直径直径直径直径直径直径直径直径直径系统,可以通过直径直径直径直径直径直径直径直径直径直定位系统。