Outputs (19)

Multi-hierarchy interaction control of a redundant robot using impedance learning (2020)
Journal Article
Jiang, Y., Yang, C., Wang, Y., Ju, Z., Li, Y., & Su, C. (2020). Multi-hierarchy interaction control of a redundant robot using impedance learning. Mechatronics, 67, Article 102348. https://doi.org/10.1016/j.mechatronics.2020.102348

The control of robots with a compliant joint motion is important for reducing collision forces and improving safety during human robot interactions. In this paper, a multi-hierarchy control framework is proposed for the redundant robot to enable the... Read More about Multi-hierarchy interaction control of a redundant robot using impedance learning.

Admittance-based controller design for physical human-robot interaction in the constrained task space (2020)
Journal Article
He, W., Xue, C., Yu, X., Li, Z., & Yang, C. (2020). Admittance-based controller design for physical human-robot interaction in the constrained task space. IEEE Transactions on Automation Science and Engineering, 17(4), 1937-1949. https://doi.org/10.1109/tase.2020.2983225

In this article, an admittance-based controller for physical human-robot interaction (pHRI) is presented to perform the coordinated operation in the constrained task space. An admittance model and a soft saturation function are employed to generate a... Read More about Admittance-based controller design for physical human-robot interaction in the constrained task space.

A method of motion recognition based on electromyographic signals (2020)
Journal Article
Luo, J., Liu, C., Feng, Y., & Yang, C. (2020). A method of motion recognition based on electromyographic signals. Advanced Robotics, 34(15), 976-984. https://doi.org/10.1080/01691864.2020.1750480

In a robot-assisted surgery, a skillful surgeon can perform the operation excellently through flexible wrist motions and rich experience. However, there are little researches about the relationship between the wrist motion and electromyography (EMG)... Read More about A method of motion recognition based on electromyographic signals.

Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models (2020)
Journal Article
Zhang, T., Lin, H., Ju, Z., & Yang, C. (2020). Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models. International Journal of Fuzzy Systems, 22, 1330-1341. https://doi.org/10.1007/s40815-020-00825-w

© 2020, The Author(s). Hand gesture is one of the most intuitive and natural ways for human to communicate with computers, and it has been widely adopted in many human–computer interaction applications. However, it is still a challenging problem when... Read More about Hand gesture recognition in complex background based on convolutional pose machine and fuzzy gaussian mixture models.

Reinforcement learning control of a flexible two-link manipulator: an experimental investigation (2020)
Journal Article
He, W., Gao, H., Zhou, C., Yang, C., & Li, Z. (2021). Reinforcement learning control of a flexible two-link manipulator: an experimental investigation. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(12), 7326-7336. https://doi.org/10.1109/TSMC.2020.2975232

This article discusses the control design and experiment validation of a flexible two-link manipulator (FTLM) system represented by ordinary differential equations (ODEs). A reinforcement learning (RL) control strategy is developed that is based on a... Read More about Reinforcement learning control of a flexible two-link manipulator: an experimental investigation.

Information entropy-based intention prediction of aerial targets under uncertain and incomplete information (2020)
Journal Article
Zhou, T., Chen, M., Wang, Y., He, J., & Yang, C. (2020). Information entropy-based intention prediction of aerial targets under uncertain and incomplete information. Entropy, 22(3), Article 279. https://doi.org/10.3390/e22030279

© 2020 by authors. To improve the effectiveness of air combat decision-making systems, target intention has been extensively studied. In general, aerial target intention is composed of attack, surveillance, penetration, feint, defense, reconnaissance... Read More about Information entropy-based intention prediction of aerial targets under uncertain and incomplete information.

Mixed reality enhanced user interactive path planning for omnidirectional mobile robot (2020)
Journal Article
Wu, M., Dai, S., & Yang, C. (2020). Mixed reality enhanced user interactive path planning for omnidirectional mobile robot. Applied Sciences, 10(3), Article 1135. https://doi.org/10.3390/app10031135

This paper proposes a novel control system for the path planning of an omnidirectional mobile robot based on mixed reality. Most research on mobile robots is carried out in a completely real environment or a completely virtual environment. However, a... Read More about Mixed reality enhanced user interactive path planning for omnidirectional mobile robot.

A sEMG-based shared control system with no-target obstacle avoidance for omnidirectional mobile robots (2020)
Journal Article
Kong, H., Yang, C., Li, G., & Dai, S. (2020). A sEMG-based shared control system with no-target obstacle avoidance for omnidirectional mobile robots. IEEE Access, 8, 26030-26040. https://doi.org/10.1109/access.2020.2970468

We propose a novel shared control strategy for mobile robots in a human-robot interaction manner based on surface eletromyography (sEMG) signals. For security reasons, an obstacle avoidance scheme is introduced to the shared control system as collisi... Read More about A sEMG-based shared control system with no-target obstacle avoidance for omnidirectional mobile robots.

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.