Relative Localization of Mobile Robots with Multiple Ultra-WideBand Ranging Measurements

Abstract

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.

NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models

“…They also take the absence of an existing infrastructure into consideration and achieve an accuracy of 2.6 m in a realworld experiment. Apart from pedestrians, robots in complicated underground or indoor environments are a noteworthy research field [31][32][33].…”

Experimental Investigation of Relative Localization Estimation in a Coordinated Formation Control of Low-Cost Underwater Drones

“…The distance between the AUVs was estimated by using the geometry of the relative positions of the beacons on the image and the beacon’s location on the target AUV. In [ 20 ], the relative localization of mobile robots based on multiple ultra-wideband ranging measurements was studied and applied to a group of ground mobile robots. In addition, there is a technique being researched and developed called SLAM (simultaneous localization and mapping).…”

Posture algorithm for mobile robot based on ultrawide band

“…The location accuracy is improved by utilizing the odometry constraints through a sliding window-based optimization. 18 Zhao et al combined the UWB and inertial navigation sensor (INS) to form a coupled UWB/INS localization framework, in which a minimum variance unbiased finite impulse response (MVU FIR) method is applied to obtain accurate position and velocity estimations from noisy measurements. The simulated and experimental results show that the MVU FIR filter exhibits better immunity to the errors about a priori knowledge of noise variances.…”