The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B2-2020
12 Aug 2020
 | 12 Aug 2020


B. Vishnyakov, Y. Blokhinov, I. Sgibnev, V. Sheverdin, A. Sorokin, A. Nikanorov, P. Masalov, K. Kazakhmedov, S. Brianskiy, Е. Andrienko, and Y. Vizilter

Keywords: multi-sensor platform, autonomous vehicle, SLAM, CNN, dynamic scene analysis, semantic segmentation, off-road, autonomous driving, camera calibration, LiDAR calibration

Abstract. In this paper we describe a new multi-sensor platform for data collection and algorithm testing. We propose a couple of methods for solution of semantic scene understanding problem for land autonomous vehicles. We describe our approaches for automatic camera and LiDAR calibration; three-dimensional scene reconstruction and odometry calculation; semantic segmentation that provides obstacle recognition and underlying surface classification; object detection; point cloud segmentation. Also, we describe our virtual simulation complex based on Unreal Engine, that can be used for both data collection and algorithm testing. We collected a large database of field and virtual data: more than 1,000,000 real images with corresponding LiDAR data and more than 3,500,000 simulated images with corresponding LiDAR data. All proposed methods were implemented and tested on our autonomous platform; accuracy estimates were obtained on the collected database.