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 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-内皮光学-UWB国家群评估系统。 为了解决可观察性、复杂初始化、准确性不足和全球一致性缺乏等问题,我们引入了全向感知系统,作为Omni-swarm的前端,由全向感应器组成,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(VIO)、多轨道地图本地化和视觉物体探测器。一个基于图的优化和前向传播系统,作为Omni-swarm的后端,将测量与前端相融合。根据实验结果,拟议的全向全向方向的全向状态估算方法,包括立式鱼眼摄影摄像相机和超广域传感器传感器(UWB)以及算法,其中包括鱼眼视视惯性惯性惯性惯性惯性惯性奥测量(VI)、多式本地地图定位定位和直径直径直径直径直径定位的外部估算,同时,可以确保整个空中定位的外部测图。