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Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR
Scanning our surroundings has become one of the key challenges in automation. Effective and efficient position, distance and velocity sensing is key to accurate decision making in automated applications from robotics to driverless cars. Light detection and ranging (LiDAR) has become a key tool in th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437189/ https://www.ncbi.nlm.nih.gov/pubmed/30918273 http://dx.doi.org/10.1038/s41598-019-41598-z |
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author | Radwell, Neal Selyem, Adam Mertens, Lena Edgar, Matthew P. Padgett, Miles J. |
author_facet | Radwell, Neal Selyem, Adam Mertens, Lena Edgar, Matthew P. Padgett, Miles J. |
author_sort | Radwell, Neal |
collection | PubMed |
description | Scanning our surroundings has become one of the key challenges in automation. Effective and efficient position, distance and velocity sensing is key to accurate decision making in automated applications from robotics to driverless cars. Light detection and ranging (LiDAR) has become a key tool in these 3D sensing applications, where the time-of-flight (TOF) of photons is used to recover distance information. These systems typically rely on scanning of a laser spot to recover position information. Here we demonstrate a hybrid LiDAR approach which combines a multi-view camera system for position and distance information, and a simple (scanless) LiDAR system for velocity tracking and depth accuracy. We show that we are able to combine data from the two component systems to provide a compound image of a scene with position, depth and velocity data at more than 1 frame per second with depth accuracy of 2.5 cm or better. This hybrid approach avoids the bulk and expense of scanning systems while adding velocity information. We hope that this approach will offer a simpler, more robust alternative to 3D scanning systems for autonomous vehicles. |
format | Online Article Text |
id | pubmed-6437189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64371892019-04-03 Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR Radwell, Neal Selyem, Adam Mertens, Lena Edgar, Matthew P. Padgett, Miles J. Sci Rep Article Scanning our surroundings has become one of the key challenges in automation. Effective and efficient position, distance and velocity sensing is key to accurate decision making in automated applications from robotics to driverless cars. Light detection and ranging (LiDAR) has become a key tool in these 3D sensing applications, where the time-of-flight (TOF) of photons is used to recover distance information. These systems typically rely on scanning of a laser spot to recover position information. Here we demonstrate a hybrid LiDAR approach which combines a multi-view camera system for position and distance information, and a simple (scanless) LiDAR system for velocity tracking and depth accuracy. We show that we are able to combine data from the two component systems to provide a compound image of a scene with position, depth and velocity data at more than 1 frame per second with depth accuracy of 2.5 cm or better. This hybrid approach avoids the bulk and expense of scanning systems while adding velocity information. We hope that this approach will offer a simpler, more robust alternative to 3D scanning systems for autonomous vehicles. Nature Publishing Group UK 2019-03-27 /pmc/articles/PMC6437189/ /pubmed/30918273 http://dx.doi.org/10.1038/s41598-019-41598-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Radwell, Neal Selyem, Adam Mertens, Lena Edgar, Matthew P. Padgett, Miles J. Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title | Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title_full | Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title_fullStr | Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title_full_unstemmed | Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title_short | Hybrid 3D ranging and velocity tracking system combining multi-view cameras and simple LiDAR |
title_sort | hybrid 3d ranging and velocity tracking system combining multi-view cameras and simple lidar |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437189/ https://www.ncbi.nlm.nih.gov/pubmed/30918273 http://dx.doi.org/10.1038/s41598-019-41598-z |
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