A Hyper-Network Based End-to-End Visual Servoing With Arbitrary Desired Poses

Author:

Yu Hongxiang1ORCID,Chen Anzhe1,Xu Kechun1ORCID,Zhou Zhongxiang1ORCID,Jing Wei2ORCID,Wang Yue1ORCID,Xiong Rong1ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China

2. Alibaba Group, Hangzhou, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. CNS: Correspondence Encoded Neural Image Servo Policy;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Adapting for Calibration Disturbances: A Neural Uncalibrated Visual Servoing Policy;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Uncalibrated 6-DoF Robotic Grasping With RGB-D Sensor: A Keypoint-Driven Servoing Method;IEEE Sensors Journal;2024-04-01

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