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All Outputs (3)

Learning compliant robotic movements based on biomimetic motor adaptation (2020)
Journal Article
Zeng, C., Chen, X., Wang, N., & Yang, C. (2021). Learning compliant robotic movements based on biomimetic motor adaptation. Robotics and Autonomous Systems, 135, Article 103668. https://doi.org/10.1016/j.robot.2020.103668

It is one of the great challenges for a robot to learn compliant movements in interaction tasks. The robot can easily acquire motion skills from a human tutor by kinematics demonstration, however, this becomes much more difficult when it comes to the... Read More about Learning compliant robotic movements based on biomimetic motor adaptation.

Neural learning enhanced variable admittance control for human-robot collaboration (2020)
Journal Article
Chen, X., Wang, N., Cheng, H., & Yang, C. (2020). Neural learning enhanced variable admittance control for human-robot collaboration. IEEE Access, 8, 25727-25737. https://doi.org/10.1109/access.2020.2969085

© 2013 IEEE. In this paper, we propose a novel strategy for human-robot impedance mapping to realize an effective execution of human-robot collaboration. The endpoint stiffness of the human arm impedance is estimated according to the configurations o... Read More about Neural learning enhanced variable admittance control for human-robot collaboration.

A framework of hybrid force/motion skills learning for robots (2020)
Journal Article
Wang, N., Chen, C., & Nuovo, A. D. (2021). A framework of hybrid force/motion skills learning for robots. IEEE Transactions on Cognitive and Developmental Systems, 13(1), 162-170. https://doi.org/10.1109/tcds.2020.2968056

Human factors and human-centered design philosophy are highly desired in today's robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more lik... Read More about A framework of hybrid force/motion skills learning for robots.