Relative Localization of Mobile Robots with Multiple Ultra-WideBand Ranging Measurements
This work addresses a crucial challenge for autonomous robots in infrastructure-less environments like emergency response, though it appears incremental as it builds on existing UWB-based methods.
The paper tackles the problem of estimating relative pose (displacement and orientation) between mobile robots using multiple Ultra-WideBand ranging nodes, achieving improved localization accuracy by minimizing ranging errors and incorporating odometry constraints through optimization and particle filtering.
Relative localization between autonomous robots without infrastructure is crucial to achieve their navigation, path planning, and formation in many applications, such as emergency response, where acquiring a prior knowledge of the environment is not possible. The traditional Ultra-WideBand (UWB)-based approach provides a good estimation of the distance between the robots, but obtaining the relative pose (including the displacement and orientation) remains challenging. We propose an approach to estimate the relative pose between a group of robots by equipping each robot with multiple UWB ranging nodes. We determine the pose between two robots by minimizing the residual error of the ranging measurements from all UWB nodes. To improve the localization accuracy, we propose to utilize the odometry constraints through a sliding window-based optimization. The optimized pose is then fused with the odometry in a particle filtering for pose tracking among a group of mobile robots. We have conducted extensive experiments to validate the effectiveness of the proposed approach.