The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 199–203, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-199-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 199–203, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-199-2020

  06 Aug 2020

06 Aug 2020

SYSTEMATIC EVALUATION AND CHARACTERIZATION OF 3D SOLID STATE LIDAR SENSORS FOR AUTONOMOUS GROUND VEHICLES

A. K. Aijazi, L. Malaterre, L. Trassoudaine, and P. Checchin A. K. Aijazi et al.
  • Institut Pascal, UMR 6602, Universit´e Clermont Auvergne, CNRS, SIGMA Clermont, F-63000 Clermont-Ferrand, France

Keywords: Solid state LiDAR, Characterization, 3D point clouds, Object detection, Segmentation and classification

Abstract. 3D LiDAR sensors play an important part in several autonomous navigation and perception systems with the technology evolving rapidly over time. This work presents the preliminary evaluation results of a 3D solid state LiDAR sensor. Different aspects of this new type of sensor are studied and their data are characterized for their effective utilization for object detection for the application of Autonomous Ground Vehicles (AGV). The paper provides a set of evaluations to analyze the characterizations and performances of such LiDAR sensors. After characterization of the sensor, the performance is also evaluated in real environment with the sensors mounted on top of a vehicle and used to detect and classify different objects using a state-of-the-art Super-Voxel based method. The 3D point cloud obtained from the sensor is classified into three main object classes “Building”, “Ground” and “Obstacles”. The results evaluated on real data, clearly demonstrate the applicability and suitability of the sensor for such type of applications.