Knowledge Commons of Institute of Automation,CAS
Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle | |
Li Ji-Yong1; Zhou Hao1; Huang Hai1; Yang Xu2; Wan Zhaoliang1; Wan Lei1 | |
发表期刊 | IEEE ACCESS |
ISSN | 2169-3536 |
2018 | |
卷号 | 6页码:73871-73884 |
通讯作者 | Huang Hai(haihus@163.com) |
摘要 | Robot machine capture protein seafood like sea cucumber and seashell is expected to play a great role in food economy improvement and divers protection. In order to realize robot capture, a sea organism absorptive type remotely operated vehicle (ROV) has been designed with the pilot operation and vision-based autonomous capture modes. A novel region-based fully convolutional network with deformable convolutional networks has been developed to realize organism target recognition. The comparisons in offline experiments have verified its advantages. In order to realize organism target following and capture control, a novel learning-based type-II fuzzy controller has been developed. Through online fuzzy rule optimization and learning, the controller can realize organism target following and capture control under image coordinate without vehicle horizontal velocity or position information in the complicated submarine environment. Field trials have been made in the Zhangzidao Island of China with the designed absorptive type ROV. The trials manifest that the designed absorptive type ROV can realize online organism target recognition, following and capture in the real submarine environment. |
关键词 | Remotely operated vehicle vision servo control target recognition |
DOI | 10.1109/ACCESS.2018.2880413 |
关键词[WOS] | UNDERWATER ; MANIPULATION ; TRACKING ; ROBOTS ; NAVIGATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61633009] ; National Natural Science Foundation of China[51579053] ; National Natural Science Foundation of China[5129050] ; National Natural Science Foundation of China[51779052] ; National Natural Science Foundation of China[51779059] ; Key Basic Research Project of Shanghai Science and Technology Innovation Plan[15JC1403300] ; Field Fund of the 13th Five-Year Plan for the Equipment Pre-Research Fund[61403120301] ; National Natural Science Foundation of China[61633009] ; National Natural Science Foundation of China[51579053] ; National Natural Science Foundation of China[5129050] ; National Natural Science Foundation of China[51779052] ; National Natural Science Foundation of China[51779059] ; Key Basic Research Project of Shanghai Science and Technology Innovation Plan[15JC1403300] ; Field Fund of the 13th Five-Year Plan for the Equipment Pre-Research Fund[61403120301] |
项目资助者 | National Natural Science Foundation of China ; Key Basic Research Project of Shanghai Science and Technology Innovation Plan ; Field Fund of the 13th Five-Year Plan for the Equipment Pre-Research Fund |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:000454366000001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/25648 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Huang Hai |
作者单位 | 1.Harbin Engn Univ, Natl Key Lab Sci & Technol Underwater Vehicle, Harbin 150001, Heilongjiang, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Li Ji-Yong,Zhou Hao,Huang Hai,et al. Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle[J]. IEEE ACCESS,2018,6:73871-73884. |
APA | Li Ji-Yong,Zhou Hao,Huang Hai,Yang Xu,Wan Zhaoliang,&Wan Lei.(2018).Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle.IEEE ACCESS,6,73871-73884. |
MLA | Li Ji-Yong,et al."Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle".IEEE ACCESS 6(2018):73871-73884. |
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