Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89040
Title: Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles
Authors: Mou, Xiaozheng
Wang, Han
Keywords: Obstacle Mapping
Wide-baseline Stereo
Issue Date: 2018
Source: Mou, X., & Wang, H. (2018). Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles. Sensors, 18(4), 1085-.
Series/Report no.: Sensors
Abstract: 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.
URI: https://hdl.handle.net/10356/89040
http://hdl.handle.net/10220/44757
ISSN: 1424-8220
DOI: http://dx.doi.org/10.3390/s18041085
Rights: © 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/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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