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Doppler-only Single-scan 3D Vehicle Odometry
Machine Perception and Intelligent Robotics (MAPIR) Group, System Engineering and Automation Department, University of Malaga, Spain.ORCID iD: 0000-0001-5853-0838
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO), AASS research centre)ORCID iD: 0000-0001-8393-9969
Örebro University, School of Science and Technology. (Mobile Robotics & Olfaction (MRO), AASS research centre)ORCID iD: 0000-0001-8658-2985
Machine Perception and Intelligent Robotics (MAPIR) Group, System Engineering and Automation Department, University of Malaga, Spain.ORCID iD: 0000-0002-9929-5309
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2024 (English)In: 2024 IEEE International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Society, 2024, p. 13703-13709Conference paper, Published paper (Refereed)
Abstract [en]

We present a novel 3D odometry method that recovers the full motion of a vehicle only from a Doppler-capable range sensor. It leverages the radial velocities measured from the scene, estimating the sensor’s velocity from a single scan. The vehicle’s 3D motion, defined by its linear and angular velocities, is calculated taking into consideration its kinematic model which provides a constraint between the velocity measured at the sensor frame and the vehicle frame.Experiments carried out prove the viability of our single-sensor method compared to mounting an additional IMU. Our method provides a more reliable translation of the sensor, compared to the errors linked to IMUs due to noise and biases. Its short-term accuracy and fast operation (∼5ms) make it a proper candidate to supply the initialization to more complex localization algorithms or mapping pipelines. Not only does it reduce the error of the mapper, but it does so at a comparable level of accuracy as an IMU would. All without the need to mount and calibrate an extra sensor on the vehicle.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2024. p. 13703-13709
Keywords [en]
Accuracy, Three-dimensional displays, Roads, Heuristic algorithms, Pipelines, Kinematics, Odometry, Localization, Range Sensing, Autonomous Vehicle Navigation, Range Odometry, Radar, Doppler
National Category
Robotics and automation
Research subject
Computer Science; Electrical Engineering
Identifiers
URN: urn:nbn:se:oru:diva-118182DOI: 10.1109/ICRA57147.2024.10611199ISI: 001369728003087Scopus ID: 2-s2.0-85202437431ISBN: 9798350384574 (electronic)ISBN: 9798350384581 (print)OAI: oai:DiVA.org:oru-118182DiVA, id: diva2:1925704
Conference
2024 IEEE International Conference on Robotics and Automation (ICRA 2024), Yokohama, Japan, May 13-17, 2024
Note

This work has been supported by the grant program PRE2018-085026 and the research project ARPEGGIO (PID2020-117057GB-I00), all funded by the Spanish Government.

Available from: 2025-01-09 Created: 2025-01-09 Last updated: 2025-03-11Bibliographically approved

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Kubelka, VladimírMagnusson, Martin

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Galeote-Luque, AndresKubelka, VladimírMagnusson, MartinRuiz-Sarmiento, Jose-RaulGonzalez-Jimenez, Javier
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