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Proceedings Paper

Localization and mapping performance of two LiDAR systems in unstructured environments
Author(s): Sam Kysar; Derek J. Chopp; Akhil M. Kurup; Joseph Rice; Jeremy P. Bos; Darrell Robinette
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Paper Abstract

For autonomous systems and vehicles to be able to traverse and path plan in their environment, location needs to be known. To determine location, two items are required, a map and a localization method. The purpose of this paper is to determine the differences and benefits between two low cost off the shelf Light Detection And Ranging (LiDAR) units in an unstructured environment for mapping and localization. The LiDAR units angularly sample the environment in a full 360-degree horizontal view, each with a varying sample density. The first has more vertical samples and a broader vertical field of view, where the other has fewer vertical samples and smaller vertical field of view but higher angular resolution. Also, both LiDAR units produce similar orders of magnitude of points per second. The two LiDAR units are compared with a simulation model of the test vehicle and LiDAR units as well as real world testing. The results of the experiments show that that mapping with a higher vertical resolution LiDAR unit appears to produce a better map, whereas localization with the higher angular resolution LiDAR unit produces more consistent results overall but runs considerably slower.

Paper Details

Date Published: 2 May 2019
PDF: 15 pages
Proc. SPIE 11009, Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019, 110090L (2 May 2019); doi: 10.1117/12.2521002
Show Author Affiliations
Sam Kysar, Michigan Technological Univ. (United States)
Derek J. Chopp, Michigan Technological Univ. (United States)
Akhil M. Kurup, Michigan Technological Univ. (United States)
Joseph Rice, Michigan Technological Univ. (United States)
Jeremy P. Bos, Michigan Technological Univ. (United States)
Darrell Robinette, Michigan Technological Univ. (United States)

Published in SPIE Proceedings Vol. 11009:
Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019
Michael C. Dudzik; Jennifer C. Ricklin, Editor(s)

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