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x-RIO: Radar Inertial Odometry with Multiple Radar Sensors and Yaw Aiding

Doer, C. 1; Trommer, G. F. 1
1 Institut für Regelungs- und Steuerungssysteme (IRS), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

A robust and accurate real-time navigation system is crucial for autonomous robotics. In particular, GNSS denied and poor visual conditions are still very challenging as vision based approaches tend to fail in darkness, direct sunlight, fog, or smoke. Therefore, we are taking advantage of inertial data and FMCW radar sensors as both are not affected by such conditions. In this work, we propose a framework, which uses several 4D mmWave radar sensors simultaneously. The extrinsic calibration of each radar sensor is estimated online. Based on a single radar scan, the 3D ego velocity and optionally yaw measurements based on Manhattan world assumptions are fused. An extensive evaluation with real world datasets is presented. We achieve even better accuracies than state of the art stereo Visual Inertial Odometry (VIO) while being able to cope with degraded visual conditions and requiring only very little computational resources.


Originalveröffentlichung
DOI: 10.1134/S2075108721040039
Scopus
Zitationen: 8
Dimensions
Zitationen: 13
Zugehörige Institution(en) am KIT Institut für Regelungs- und Steuerungssysteme (IRS)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2021
Sprache Englisch
Identifikator ISSN: 2075-1087, 2075-1109
KITopen-ID: 1000143699
Erschienen in Gyroscopy and Navigation
Verlag Springer-Verlag
Band 12
Heft 4
Seiten 329–339
Nachgewiesen in Scopus
Dimensions
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