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Range-aided ego-centric collaborative pose estimation for multiple robots
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-6415-6982
Research and Development Engineer at the Autonomous Driving Lab in Scania Group, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2022 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 202, article id 117052Article in journal (Refereed) Published
Abstract [en]

Robots’ simultaneous relative pose estimation has become an essential step in most robotic-oriented problems, such as map merging, collision avoidance, path planning, and multi-Simultaneous Localization and Mapping (SLAM). This article addresses the problem of 3D and ego-centric relative pose estimation for a team of robots equipped with Ultra WideBand (UWB) nodes. More specifically, the article introduces a novel optimization framework to obtain pose information based on the embodiment of UWB ranges, without relying on any fixed external infrastructure configuration of UWB anchors on the surrounding environment. In the proposed method, we demonstrate the validity through the utilization of a Micro Aerial Vehicle (MAV) and a ground vehicle that are equipped with multiple UWB transceivers, and each platform simultaneously acts as a based anchor for the other platform for extracting an ego-centric position estimation of the UWB nodes. Additionally, for the pose estimation, the obtained information is fused with the onboard Inertial Measurement Unit (IMU) measurements on each of the considered robotic platforms. Finally, the efficacy of the proposed theoretical framework is evaluated in multiple experiments, where the aerial and ground platforms are simultaneously and separately navigating, and the ego-centric collaborative pose-estimation is compared with a VICON ground truth positioning system.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 202, article id 117052
Keywords [en]
Relative pose estimation, UWB, Ego-centric estimation, Sensor fusion
National Category
Computer graphics and computer vision Signal Processing
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-90325DOI: 10.1016/j.eswa.2022.117052ISI: 000804926500005Scopus ID: 2-s2.0-85129526790OAI: oai:DiVA.org:ltu-90325DiVA, id: diva2:1653326
Funder
EU, Horizon 2020, 869379 illuMINEation
Note

Validerad;2022;Nivå 2;2022-05-31 (hanlid)

Available from: 2022-04-21 Created: 2022-04-21 Last updated: 2025-02-01Bibliographically approved

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Papadimitriou, AndreasNikolakopoulos, George

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