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Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework

文献类型：期刊论文

作者Meng, Yan2,3; Wu, Zhengxing2,3; Zhang, Pengfei2,3; Wang, Jian2,3; Yu, Junzhi1,3
刊名IEEE-ASME TRANSACTIONS ON MECHATRONICS
出版日期2022-03-11
页码12
关键词Robots Cameras Robot vision systems Streaming media Bio-inspired robotics Real-time systems Estimation Bioinspired robot digital video stabilization estimation-and-prediction framework robotic fish vision system
ISSN号1083-4435
DOI10.1109/TMECH.2022.3155696
通讯作者Yu, Junzhi(junzhi.yu@ia.ac.cn)
英文摘要The rhythmic movement of bioinspired robotic fish brings about undesirable visual jitter. Note that the unstable camera path of this kind of robot is characterized by obvious regularity and predictability, of which traditional stabilization methods have not made full advantage. This article proposes a novel estimation-and-prediction framework for real-time digital video stabilization of bioinspired robotic fish. First, based on the attitude information of an inertial measurement unit (IMU), a camera-IMU model is established, where the homography transformation with eight degrees of freedom (DOFs) is reduced to translation transformation with two DOFs. Second, traditional optical flow and gray projection methods as well as a novel translation estimation network are employed to estimate the translations between consecutive frames. Third, a lightweight long short-term memory (LSTM) network is constructed, allowing remarkable prediction and smoothing of the camera path. Finally, aquatic experiments under various scenarios are conducted on a manta-inspired robot, demonstrating the effectiveness of the proposed method. Specifically, compared with the state-of-the-art commercial offline stabilization software, our online stabilization algorithm achieves approximate visual stability and remarkably faster stabilization speed. The obtained results shed light on visual sensing and control applications of bioinspired underwater vehicles.
资助项目National Natural Science Foundation of China[61973303] ; National Natural Science Foundation of China[62033013] ; National Natural Science Foundation of China[61725305] ; National Natural Science Foundation of China[U1909206] ; National Natural Science Foundation of China[62022090] ; Beijing Natural Science Foundation[4192060] ; Beijing Nova Program[Z201100006820078] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[2019138]
WOS研究方向Automation & Control Systems ; Engineering
语种英语
WOS记录号WOS:000770572900001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Nova Program ; Youth Innovation Promotion Association, Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/48111]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
复杂系统管理与控制国家重点实验室_水下机器人
通讯作者Yu, Junzhi
作者单位1.Peking Univ, Coll Engn, Beijing Innovat Ctr Engn Sci & Adv Technol, Dept Adv Mfg & Robot,State Key Lab Turbulence & C, Beijing 100871, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.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		 Meng, Yan,Wu, Zhengxing,Zhang, Pengfei,et al. Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2022:12.
APA Meng, Yan,Wu, Zhengxing,Zhang, Pengfei,Wang, Jian,&Yu, Junzhi.(2022).Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework.IEEE-ASME TRANSACTIONS ON MECHATRONICS,12.
MLA Meng, Yan,et al."Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2022):12.

入库方式： OAI收割

来源：自动化研究所

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