Characterizing Perspective Error in Voxel-Based Lidar Scan Matching

Fuente: arXiv
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Hauptverfasser: Rife, Jason, McDermott, Matthew
Format: Preprint
Veröffentlicht: 2024
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author Rife, Jason
McDermott, Matthew
author_facet Rife, Jason
McDermott, Matthew
contents This paper quantifies an error source that limits the accuracy of lidar scan matching, particularly for voxel-based methods. Lidar scan matching, which is used in dead reckoning (also known as lidar odometry) and mapping, computes the rotation and translation that best align a pair of point clouds. Perspective errors occur when a scene is viewed from different angles, with different surfaces becoming visible or occluded from each viewpoint. To explain perspective anomalies observed in data, this paper models perspective errors for two objects representative of urban landscapes: a cylindrical column and a dual-wall corner. For each object, we provide an analytical model of the perspective error for voxel-based lidar scan matching. We then analyze how perspective errors accumulate as a lidar-equipped vehicle moves past these objects.
format Preprint
id arxiv_https___arxiv_org_abs_2401_13416
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Characterizing Perspective Error in Voxel-Based Lidar Scan Matching
Rife, Jason
McDermott, Matthew
Robotics
This paper quantifies an error source that limits the accuracy of lidar scan matching, particularly for voxel-based methods. Lidar scan matching, which is used in dead reckoning (also known as lidar odometry) and mapping, computes the rotation and translation that best align a pair of point clouds. Perspective errors occur when a scene is viewed from different angles, with different surfaces becoming visible or occluded from each viewpoint. To explain perspective anomalies observed in data, this paper models perspective errors for two objects representative of urban landscapes: a cylindrical column and a dual-wall corner. For each object, we provide an analytical model of the perspective error for voxel-based lidar scan matching. We then analyze how perspective errors accumulate as a lidar-equipped vehicle moves past these objects.
title Characterizing Perspective Error in Voxel-Based Lidar Scan Matching
topic Robotics
url https://arxiv.org/abs/2401.13416