Achieving collaborative tasks in multi-robot teams requires knowledge of the relative poses of a robot's neighbours. Ultra-wideband (UWB) systems are becoming increasingly popular as a means of inter-robot ranging and communication. A major constraint associated with UWB is that only one pair of UWB transceivers can range at a time to avoid interference, hence hindering the scalability of UWB-based localization and requiring complex scheduling algorithms. In this paper, a novel ranging protocol is proposed that allows all robots to passively listen on neighbouring communicating robots without any hierarchical restrictions on the role of the robots. This is then utilized to allow each robot to obtain more range measurements, broadcast preintegrated inertial measurement unit (IMU) measurements for relative pose state estimation directly on SE2(3), and to propose a simple media-access control (MAC) protocol to avoid interference. Consequently, a simultaneous clock-synchronization and relative-pose estimator (CSRPE) is then formulated using an on-manifold extended Kalman filter (EKF) and is evaluated in simulation using Monte-Carlo runs for up to 7 robots. Additionally, the proposed ranging protocol is implemented in C on custom-made UWB boards fitted to quadcopters, and the proposed filter is then evaluated over multiple experimental trials for 3 quadcopters, yielding up to 55% improvement in localization accuracy when using passive listening.

翻译：实现多机器人团队的协同任务需要了解机器人邻居的相对位姿。超宽带（UWB）系统作为机器人间测距与通信的手段日益普及。UWB的一个主要限制是，为避免干扰，同一时间只能有一对UWB收发器进行测距，这阻碍了基于UWB的定位的可扩展性，并需要复杂的调度算法。本文提出了一种新颖的测距协议，允许所有机器人无层级限制地被动监听邻近通信机器人。该协议进而被用于使每个机器人获取更多测距测量值，广播预积分的惯性测量单元（IMU）测量值以直接在SE2(3)上进行相对位姿状态估计，并提出一种简单的介质访问控制（MAC）协议以避免干扰。随后，利用流形上的扩展卡尔曼滤波器（EKF）构建了同时时钟同步与相对位姿估计器（CSRPE），并通过蒙特卡洛仿真对多达7个机器人进行了评估。此外，所提测距协议已在配备于四旋翼飞行器的定制UWB板卡上用C语言实现，并在3架四旋翼飞行器的多次实验中评估了所提滤波器，采用被动监听时定位精度提升高达55%。