[1]XU Xiaobin,DUAN Haibin,ZENG Zhigang.Cooperative tracking of unmanned surface vessels at sea inspired by a multi-resolution mechanism of raptor vision[J].CAAI Transactions on Intelligent Systems,2023,18(4):867-877.[doi:10.11992/tis.202211001]
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Cooperative tracking of unmanned surface vessels at sea inspired by a multi-resolution mechanism of raptor vision

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 18 Number of periods: 2023 4 Page number: 867-877 Column: 吴文俊人工智能科学技术奖论坛 Public date: 2023-07-15
Title:
Cooperative tracking of unmanned surface vessels at sea inspired by a multi-resolution mechanism of raptor vision
Author(s):
XU Xiaobin1;  DUAN Haibin1;  ZENG Zhigang2
1. Bio-inspired Autonomous Flight Systems Research Group, State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100083, China;
2. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Keywords:
raptor vision; fovea; multi-resolution; large and small scenes; competitive selection; saliency detection; collaborative strategy; unmanned surface vessel tracking
CLC:
TP391；V249.122
DOI:
10.11992/tis.202211001
Abstract:
In this paper, a cooperative tracking method of unmanned surface vessel (USV) at sea inspired by a multi-resolution mechanism of raptor vision is proposed to solve the contradiction between large scene and high resolution at sea. The large and small scenes of the target USV tracking are built based on the multi-resolution imaging rules of dual fovea of raptor vision. In the large scene, the competitive selection mechanism in the optic tectum- nucleus isthmi pathway of raptor is employed to detect the saliency target of USV. The detection results are applied to correct the tracking position of kernel correlation filter. In the small scene, the color resolution space imitating raptor is built, and the cooperative target on the USV is obtained by the color saliency detection method. The cooperative tracking strategy with large scene correction and small scene guiding is established to achieve cooperative tracking of USV at sea. The comparison experiment results show that the tracking success rate of the proposed method is higher than that of the comparison method. Besides, the proposed method has the highest average overlap rate and the lowest average pixel error. The proposed method is suitable for unmanned aerial vehicle(UAV) to track the USV at sea.
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