{"title":"Robust and Scalable Multi-Robot Localization Using Stereo UWB Arrays","authors":"Hanying Zhao;Lingwei Xu;Yi Li;Feiyang Wen;Haoran Gao;Changwu Liu;Jincheng Yu;Yu Wang;Yuan Shen","doi":"10.1109/TRO.2025.3587854","DOIUrl":null,"url":null,"abstract":"In environments where robots operate with limited global navigation satellite system accessibility, ultra-wideband (UWB) localization technology is a popular auxiliary solution to assist visual–inertial odometry systems. However, current UWB approaches lack 3-D pairwise localization capability and suffer from rapidly declining localization update rates as the network scales, limiting their effectiveness for swarm robotic applications. This article presents a novel UWB sensor that enables 3-D pairwise localization and a localization scheme that can deliver robust, scalable, and accurate position awareness for multi-robot systems. Our approach begins with calibrating intrinsic UWB errors from hardware deviations and propagation effects, yielding high-accuracy distance and direction measurements. Using these measurements, we perform distributed relative localization through inter- and intra-node cooperation by integrating UWB and inertial measurement unit data. To enable swarm-scale operation, our platform implements the signal-multiplexing network ranging protocol to maximize update rates and network capacity. Experimental results show that our approach achieves centimeter-level localization accuracy at high update rates (100 Hz with UWB only), validating its robustness, scalability, and accuracy for robotic applications.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"5645-5662"},"PeriodicalIF":10.5000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Robotics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11077451/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
In environments where robots operate with limited global navigation satellite system accessibility, ultra-wideband (UWB) localization technology is a popular auxiliary solution to assist visual–inertial odometry systems. However, current UWB approaches lack 3-D pairwise localization capability and suffer from rapidly declining localization update rates as the network scales, limiting their effectiveness for swarm robotic applications. This article presents a novel UWB sensor that enables 3-D pairwise localization and a localization scheme that can deliver robust, scalable, and accurate position awareness for multi-robot systems. Our approach begins with calibrating intrinsic UWB errors from hardware deviations and propagation effects, yielding high-accuracy distance and direction measurements. Using these measurements, we perform distributed relative localization through inter- and intra-node cooperation by integrating UWB and inertial measurement unit data. To enable swarm-scale operation, our platform implements the signal-multiplexing network ranging protocol to maximize update rates and network capacity. Experimental results show that our approach achieves centimeter-level localization accuracy at high update rates (100 Hz with UWB only), validating its robustness, scalability, and accuracy for robotic applications.
期刊介绍:
The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles.
Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.