[1]徐小斌,段海滨,曾志刚.仿猛禽视觉多分辨率的海上无人艇协同跟踪[J].智能系统学报,2023,18(4):867-877.[doi:10.11992/tis.202211001]
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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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]
仿猛禽视觉多分辨率的海上无人艇协同跟踪
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
18
期数:
2023年第4期
页码:
867-877
栏目:
吴文俊人工智能科学技术奖论坛
出版日期:
2023-07-15
- Title:
- Cooperative tracking of unmanned surface vessels at sea inspired by a multi-resolution mechanism of raptor vision
- Keywords:
- raptor vision; fovea; multi-resolution; large and small scenes; competitive selection; saliency detection; collaborative strategy; unmanned surface vessel tracking
- 分类号:
- TP391；V249.122
- 摘要:
- 针对海上无人艇跟踪过程中大场景与高分辨间的矛盾问题，本文提出一种仿猛禽视觉多分辨率机制的海上目标无人艇协同跟踪方法。模拟猛禽双中央凹多分辨率成像规律，构建目标无人艇跟踪大小场景；在大场景中，模拟猛禽视顶盖?峡核通路中视觉刺激的竞争选择机制进行海上无人艇显著性检测，用于纠正核相关滤波目标跟踪的结果；在小场景中，建立仿猛禽色彩分辨空间，并采用颜色显著性检测方法提取无人艇上的合作靶标；建立大场景纠正及小场景引导协同跟踪策略，实现对海上目标无人艇的协同跟踪。对比实验结果表明，本文方法的跟踪成功率高于对比方法，且有最高的平均重叠率和最低的平均像素误差，适于无人机完成对海上目标无人艇的跟踪任务。
- 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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备注/Memo
收稿日期:2022-11-02。
基金项目:国家自然科学基金项目（U1913602，91948204，U20B2071，T2121003，U19B2033）.
作者简介:徐小斌，博士研究生，主要研究方向为无人系统仿生视觉自主控制;段海滨，教授，博士生导师，国家级人才，主要研究方向为无人机自主控制、计算机仿生视觉与智能感知、仿生智能计算理论及应用，主持国家自然科学基金重大研究计划重点项目、重点项目等多项，获吴文俊人工智能科技创新一等奖。发表学术论文90 余篇，出版专著6部。;曾志刚，教授、博士生导师，国家级人才，主要研究方向为切换系统控制理论与应用、计算智能、系统稳定性等，曾获国家科技进步二等奖，主持国家自然科学基金重大研究计划重点项目、重点项目等30余项。发表学术论文300余篇。
通讯作者:段海滨.E-mail:hbduan@buaa.edu.cn
更新日期/Last Update:
1900-01-01