Abstract—Real-time relative pose (RP) estimation is a corner-stone for effective multi-agent collaboration. When conventionalglobal positioning infrastructure such as GPS is unavailable, theuse of Ultra-Wideband (UWB) technology on each agent providesa practical means to measure inter-agent range. Due to UWB{\textquoteright}sprecise range measurements and robust communication capa-bilities, external hardware installations are not needed. However,when only a single UWB device per agent is used, the relative posebetween the agents can be unobservable, resulting in a complexsolution space with multiple possible RPs. This paper proposes anovel method based on an Unscented Particle Filter (UPF) thatfuses single UWB ranges with visual-inertial odometry (VIO).The proposed decentralized method solves the multi-modal solu-tion in 3D (4-DoF) for the RP when it is unobservable. Moreover,a pseudo-state is introduced to correct the rotational drift ofthe agents. Through simulations and experiments involving tworobots, the proposed solution was shown to be competitive andless computationally expensive than state-of-the-art algorithms.Additionally, the proposed solution provides all possible relativeposes from the first measurement. The code and link to the videoare available https://github.com/y2d2/UPF RPE.
Durodié, Y, Convens, B, Liu, G, Decoster, T, Munteanu, A & Vanderborght, B 2024, 'Where Are You? Unscented Particle Filter for Single Range Relative Pose Estimation in Unobservable Motion Using UWB and VIO.', IEEE Robotics and Automation Letters, vol. 9, no. 12, 2377-3766, pp. 11754-11761. https://doi.org/10.1109/LRA.2024.3495592
Durodié, Y., Convens, B., Liu, G., Decoster, T., Munteanu, A., & Vanderborght, B. (2024). Where Are You? Unscented Particle Filter for Single Range Relative Pose Estimation in Unobservable Motion Using UWB and VIO. IEEE Robotics and Automation Letters, 9(12), 11754-11761. Article 2377-3766. https://doi.org/10.1109/LRA.2024.3495592
@article{2adced45c08446fb861200fd5208b643,
title = "Where Are You? Unscented Particle Filter for Single Range Relative Pose Estimation in Unobservable Motion Using UWB and VIO.",
abstract = "Abstract—Real-time relative pose (RP) estimation is a corner-stone for effective multi-agent collaboration. When conventionalglobal positioning infrastructure such as GPS is unavailable, theuse of Ultra-Wideband (UWB) technology on each agent providesa practical means to measure inter-agent range. Due to UWB{\textquoteright}sprecise range measurements and robust communication capa-bilities, external hardware installations are not needed. However,when only a single UWB device per agent is used, the relative posebetween the agents can be unobservable, resulting in a complexsolution space with multiple possible RPs. This paper proposes anovel method based on an Unscented Particle Filter (UPF) thatfuses single UWB ranges with visual-inertial odometry (VIO).The proposed decentralized method solves the multi-modal solu-tion in 3D (4-DoF) for the RP when it is unobservable. Moreover,a pseudo-state is introduced to correct the rotational drift ofthe agents. Through simulations and experiments involving tworobots, the proposed solution was shown to be competitive andless computationally expensive than state-of-the-art algorithms.Additionally, the proposed solution provides all possible relativeposes from the first measurement. The code and link to the videoare available https://github.com/y2d2/UPF RPE.",
keywords = "Multi-Robot Systems, Localization, Sensor Fusion",
author = "Yuri Durodi{\'e} and Bryan Convens and Gaoyuan Liu and Thomas Decoster and Adrian Munteanu and Bram Vanderborght",
note = "Funding Information: This work was supported in part by imec vzw, in part by the Research Program Artifici\u00EBle Intelligentie Vlaanderen from the Flemish Government, in part by the EU Project SPEAR under Grant 101119774, and in part by the Eurobin through the Horizon Europe framework under Grant 101070596. Funding Information: Manuscript received: June, 25, 2024; Revised August, 21, 2024; Accepted November, 6, 2024. This paper was recommended for publication by Editor Sven Behnke upon evaluation of the Associate Editor and Reviewers\u2019 comments. This work was supported by imec vzw, the research program Artifici\u00EBle Intelligentie Vlaanderen from the Flemish Government, the EU project SPEAR 101119774, and the Eurobin 101070596 grant from the Horizon Europe framework. 1Authors are with Brubotics, Vrije Universiteit Brussel, Belgium, and affiliated to imec vzw. yuri.durodie@vub.be 2 Adrian Muntenau is with ETRO, Vrije Universiteit Brussel, Belgium, and affiliated to imec vzw. Digital Object Identifier (DOI): see top of this page. Publisher Copyright: {\textcopyright} 2024 IEEE.",
year = "2024",
month = nov,
day = "24",
doi = "10.1109/LRA.2024.3495592",
language = "English",
volume = "9",
pages = "11754--11761",
journal = "IEEE Robotics and Automation Letters",
issn = "2377-3766",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",
}