Robust obstacle detection for unmanned surface vehicles

Yueming Qin; Xiuzhi Zhang

doi:10.1117/12.2285607

8 March 2018 Robust obstacle detection for unmanned surface vehicles

Yueming Qin, Xiuzhi Zhang

Proceedings Volume 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 106111E (2018) https://doi.org/10.1117/12.2285607
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Citation Download Citation

Yueming Qin and Xiuzhi Zhang "Robust obstacle detection for unmanned surface vehicles", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106111E (8 March 2018); https://doi.org/10.1117/12.2285607

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