Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle

doi:10.1109/ACCESS.2018.2880413

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Design and Vision Based Autonomous Capture of Sea Organism With Absorptive Type Remotely Operated Vehicle
	Li Ji-Yong 1; Zhou Hao 1; Huang Hai 1; Yang Xu2 ; Wan Zhaoliang 1; Wan Lei 1
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	被引频次：17[WOS] [WOS记录] [WOS相关记录]
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.