Knowledge Commons of Institute of Automation,CAS
Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework | |
Meng, Yan1,2; Wu, Zhengxing1,2; Zhang, Pengfei1,2; Wang, Jian1,2; Yu, Junzhi1,3 | |
发表期刊 | IEEE-ASME TRANSACTIONS ON MECHATRONICS |
ISSN | 1083-4435 |
2022-03-11 | |
页码 | 12 |
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. |
关键词 | Bioinspired robot digital video stabilization estimation-and-prediction framework robotic fish vision system |
DOI | 10.1109/TMECH.2022.3155696 |
收录类别 | SCI |
语种 | 英语 |
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] |
项目资助者 | National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Nova Program ; Youth Innovation Promotion Association, Chinese Academy of Sciences |
WOS研究方向 | Automation & Control Systems ; Engineering |
WOS类目 | Automation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical |
WOS记录号 | WOS:000770572900001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 智能机器人 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48112 |
专题 | 复杂系统认知与决策实验室_先进机器人 复杂系统认知与决策实验室_水下机器人 |
通讯作者 | Yu, Junzhi |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.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 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
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. |
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