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Modeling and analysis of an underwater biomimetic vehicle-manipulator system 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2022, 卷号: 65, 期号: 3, 页码: 3
作者:  Bai, Xuejian;  Wang, Yu;  Wang, Shuo;  Wang, Rui;  Tan, Min;  Wang, Wei
Adobe PDF(868Kb)  |  收藏  |  浏览/下载：244/49  |  提交时间：2021/11/04
underwater manipulation  underwater vehicle-manipulator system  
Development of a Whale-Shark-Inspired Gliding Robotic Fish With High Maneuverability 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2020, 卷号: 25, 期号: 6, 页码: 2824-2834
作者:  Dong, Huijie;  Wu, Zhengxing;  Chen, Di;  Tan, Min;  Yu, Junzhi
Adobe PDF(2542Kb)  |  收藏  |  浏览/下载：284/45  |  提交时间：2021/03/02
Buoyancy  Robot kinematics  Shape  Mechatronics  Whales  Robot sensing systems  Biomimetic robot  gliding robotic fish  modeling and control  underwater robotics  
Design of a Miniature Underwater Angle-of-Attack Sensor and Its Application to a Self-Propelled Robotic Fish 期刊论文
IEEE JOURNAL OF OCEANIC ENGINEERING, 2020, 卷号: 45, 期号: 4, 页码: 1295-1307
作者:  Yu, Junzhi;  Wang, Tianzhu;  Wu, Zhengxing;  Tan, Min
Adobe PDF(2775Kb)  |  收藏  |  浏览/下载：209/27  |  提交时间：2021/01/07
Robot sensing systems  Real-time systems  Propulsion  Magnetomechanical effects  Magnetic analysis  Sea measurements  Angle of attack (AoA)  angle sensor  measurement  robotic fish  underwater  
Investigating the dynamic memory effect of human drivers via ON-LSTM 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 9, 页码: 11
作者:  Dai, Shengzhe;  Li, Zhiheng;  Li, Li;  Cao, Dongpu;  Dai, Xingyuan;  Lin, Yilun
Adobe PDF(325Kb)  |  收藏  |  浏览/下载：240/44  |  提交时间：2020/12/04
driving behavior  memory effect  trajectory prediction  historical information  ON-LSTM  
Towards Real-Time Advancement of Underwater Visual Quality With GAN 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 卷号: 66, 期号: 12, 页码: 9350-9359
作者:  Chen, Xingyu;  Yu, Junzhi;  Kong, Shihan;  Wu, Zhengxing;  Fang, Xi;  Wen, Li
Adobe PDF(4984Kb)  |  收藏  |  浏览/下载：401/137  |  提交时间：2019/12/16
Generative adversarial networks (GAN) image restoration  machine learning  underwater vision