Assessing the Robustness of LiDAR, Radar and Depth Cameras Against Ill-Reflecting Surfaces in Autonomous Vehicles: An Experimental Study

Range-measuring sensors play a critical role in autonomous driving systems. While LiDAR technology has been dominant, its vulnerability to adverse weather conditions is well-documented. This paper focuses on secondary adverse conditions and the implications of ill-reflective surfaces on range measur...

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Bibliographic Details
Published inarXiv.org
Main Authors Loetscher, Michael, Baumann, Nicolas, Ghignone, Edoardo, Ronco, Andrea, Magno, Michele
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 19.09.2023
Subjects
Cameras
Lidar
Race cars
Reflectance
Robotics
Sensors
Weather
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Summary:Range-measuring sensors play a critical role in autonomous driving systems. While LiDAR technology has been dominant, its vulnerability to adverse weather conditions is well-documented. This paper focuses on secondary adverse conditions and the implications of ill-reflective surfaces on range measurement sensors. We assess the influence of this condition on the three primary ranging modalities used in autonomous mobile robotics: LiDAR, RADAR, and Depth-Camera. Based on accurate experimental evaluation the papers findings reveal that under ill-reflectivity, LiDAR ranging performance drops significantly to 33% of its nominal operating conditions, whereas RADAR and Depth-Cameras maintain up to 100% of their nominal distance ranging capabilities. Additionally, we demonstrate on a 1:10 scaled autonomous racecar how ill-reflectivity adversely impacts downstream robotics tasks, highlighting the necessity for robust range sensing in autonomous driving.
ISSN:2331-8422