Flexible and Resource-Efficient Multi-Robot Collaborative Visual-Inertial-Range Localization

Thien Hoang Nguyen, Thien-Minh Nguyen, Lihua Xie

Abstract: In multi-robot systems, two important research problems are relative localization between the robots and global localization of all robots in a common frame. Traditional methods rely on detecting inter and intra-robot loop closures, which can be restrictive operation-wise since the robot must form loops. Ultra-wideband sensors, which provide direct distance measurements and robot ID, can replace loop closures in many applications. However, existing research on UWB-aided multi-robot state estimation often ignores the odometry drift which leads to inaccurate global position in the long run. In this work, we present a UWB-aided multi-robot localization system that does not rely on loop closure (flexible) and only requires odometry data from neighbors (resource-efficient). We propose a two-stage approach: 1) with a long sliding window, the relative transformation is refined based on range and odometry data, 2) onboard visual-inertial-range data are tightly fused in a short-term sliding window to provide more accurate local and global estimates. Simulation and real-life experiments with two quadrotors show that the system as a whole outperforms previous approaches as well as its individual parts.