Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles
This paper proposes a wide-baseline stereo-based static obstacle mapping approach for unmanned surface vehicles (USVs). The proposed approach eliminates the complicated calibration work and the bulky rig in our previous binocular stereo system, and raises the ranging ability from 500 to 1000 m with...
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sg-ntu-dr.10356-890402020-03-07T13:57:31Z Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles Mou, Xiaozheng Wang, Han School of Electrical and Electronic Engineering Obstacle Mapping Wide-baseline Stereo This paper proposes a wide-baseline stereo-based static obstacle mapping approach for unmanned surface vehicles (USVs). The proposed approach eliminates the complicated calibration work and the bulky rig in our previous binocular stereo system, and raises the ranging ability from 500 to 1000 m with a even larger baseline obtained from the motion of USVs. Integrating a monocular camera with GPS and compass information in this proposed system, the world locations of the detected static obstacles are reconstructed while the USV is traveling, and an obstacle map is then built. To achieve more accurate and robust performance, multiple pairs of frames are leveraged to synthesize the final reconstruction results in a weighting model. Experimental results based on our own dataset demonstrate the high efficiency of our system. To the best of our knowledge, we are the first to address the task of wide-baseline stereo-based obstacle mapping in a maritime environment. Published version 2018-05-09T01:41:43Z 2019-12-06T17:16:34Z 2018-05-09T01:41:43Z 2019-12-06T17:16:34Z 2018 Journal Article Mou, X., & Wang, H. (2018). Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles. Sensors, 18(4), 1085-. 1424-8220 https://hdl.handle.net/10356/89040 http://hdl.handle.net/10220/44757 10.3390/s18041085 en Sensors © 2018 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 14 p. application/pdf |
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Obstacle Mapping Wide-baseline Stereo |
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Obstacle Mapping Wide-baseline Stereo Mou, Xiaozheng Wang, Han Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
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This paper proposes a wide-baseline stereo-based static obstacle mapping approach for unmanned surface vehicles (USVs). The proposed approach eliminates the complicated calibration work and the bulky rig in our previous binocular stereo system, and raises the ranging ability from 500 to 1000 m with a even larger baseline obtained from the motion of USVs. Integrating a monocular camera with GPS and compass information in this proposed system, the world locations of the detected static obstacles are reconstructed while the USV is traveling, and an obstacle map is then built. To achieve more accurate and robust performance, multiple pairs of frames are leveraged to synthesize the final reconstruction results in a weighting model. Experimental results based on our own dataset demonstrate the high efficiency of our system. To the best of our knowledge, we are the first to address the task of wide-baseline stereo-based obstacle mapping in a maritime environment. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Mou, Xiaozheng Wang, Han |
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Article |
author |
Mou, Xiaozheng Wang, Han |
author_sort |
Mou, Xiaozheng |
title |
Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
title_short |
Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
title_full |
Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
title_fullStr |
Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
title_full_unstemmed |
Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles |
title_sort |
wide-baseline stereo-based obstacle mapping for unmanned surface vehicles |
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2018 |
url |
https://hdl.handle.net/10356/89040 http://hdl.handle.net/10220/44757 |
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1681048126785323008 |