Multi-Robot Cooperative Localization with Single UWB Error Correction

Abstract

Deployment of multiple robots in real-world scenarios requires simultaneous information exchange from all platforms to ensure effective task performance. The robot's relative position to its peers is an important data needed to predict collision between robots or task distribution. This paper introduces a robust and simple method for achieving cooperative localization among multiple robots, utilizing a single ultra-wideband (UWB) sensor for each platform. Each robot uses a visual-inertial odometry (VIO) system to track its own trajectory. Given the inherent drift associated with VIO systems, we leverage UWB data to estimate and correct this drift, enhancing each robot's localization accuracy. Our approach substantially improves the result compared with other cooperative localization methods and can even correct the VIO ego-motion.