All Outputs (39)

DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation (2021)
Journal Article
Lu, Z., Wang, N., & Shi, D. (2022). DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation. Complex and Intelligent Systems, 8, 2873–2882. https://doi.org/10.1007/s40747-021-00429-3

Dual-arm robot manipulation is applicable to many domains, such as industrial, medical, and home service scenes. Learning from demonstrations (LfD) is a highly effective paradigm for robotic learning, where a robot learns from human actions directly... Read More about DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation.

A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks (2021)
Journal Article
Lu, Z., Wang, N., & Yang, C. (2022). A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks. International Journal of Systems Science, 53(1), 25-39. https://doi.org/10.1080/00207721.2021.1936275

Power consumption and data redundancy of wireless sensor networks (WSN) are widely considered for a distributed state monitoring network. For reducing the energy consumption and data amount, we propose a topology optimisation and an iterative paramet... Read More about A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks.

Review of the techniques used in motor‐cognitive human‐robot skill transfer (2021)
Journal Article
Guan, Y., Wang, N., & Yang, C. (2021). Review of the techniques used in motor‐cognitive human‐robot skill transfer. Cognitive Computation and Systems, 3(3), 229-252. https://doi.org/10.1049/ccs2.12025

A conventional robot programming method extensively limits the reusability of skills in the developmental aspect. Engineers programme a robot in a targeted manner for the realisation of predefined skills. The low reusability of general-purpose robot... Read More about Review of the techniques used in motor‐cognitive human‐robot skill transfer.

Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance (2021)
Journal Article
Lu, Z., & Wang, N. (2021). Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance. Assembly Automation, 41(3), 302-311. https://doi.org/10.1108/AA-11-2020-0168

Purpose: Dynamic movement primitives (DMPs) is a general robotic skill learning from demonstration method, but it is usually used for single robotic manipulation. For cloud-based robotic skill learning, the authors consider trajectories/skills change... Read More about Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance.

A review on manipulation skill acquisition through teleoperation‐based learning from demonstration (2021)
Journal Article
Si, W., Wang, N., & Yang, C. (2021). A review on manipulation skill acquisition through teleoperation‐based learning from demonstration. Cognitive Computation and Systems, 3(1), 1-16. https://doi.org/10.1049/ccs2.12005

Manipulation skill learning and generalisation have gained increasing attention due to the wide applications of robot manipulators and the spurt of robot learning techniques. Especially, the learning from demonstration method has been exploited widel... Read More about A review on manipulation skill acquisition through teleoperation‐based learning from demonstration.

Composite dynamic movement primitives based on neural networks for human–robot skill transfer (2021)
Journal Article
Si, W., Wang, N., & Yang, C. (in press). Composite dynamic movement primitives based on neural networks for human–robot skill transfer. Neural Computing and Applications, 35, 23283–23293. https://doi.org/10.1007/s00521-021-05747-8

In this paper, composite dynamic movement primitives (DMPs) based on radial basis function neural networks (RBFNNs) are investigated for robots’ skill learning from human demonstrations. The composite DMPs could encode the position and orientation ma... Read More about Composite dynamic movement primitives based on neural networks for human–robot skill transfer.

A constrained DMPs framework for robot skills learning and generalization from human demonstrations (2021)
Journal Article
Lu, Z., Wang, N., & Yang, C. (2021). A constrained DMPs framework for robot skills learning and generalization from human demonstrations. IEEE/ASME Transactions on Mechatronics, 26(6), 3265 - 3275. https://doi.org/10.1109/TMECH.2021.3057022

Dynamical movement primitives (DMPs) model is a useful tool for efficiently robotic learning manipulation skills from human demonstrations and then generalizing these skills to fulfill new tasks. It is improved and applied for the cases with multiple... Read More about A constrained DMPs framework for robot skills learning and generalization from human demonstrations.

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.

A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller (2019)
Journal Article
Wang, N., Chen, C., & Yang, C. (2020). A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller. Neurocomputing, 390, 260-267. https://doi.org/10.1016/j.neucom.2019.04.100

© 2019 Elsevier B.V. Robot learning from demonstration (LfD) enables robots to be fast programmed. This paper presents a novel LfD framework involving a teaching phase, a learning phase and a reproduction phase, and proposes methods in each of these... Read More about A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller.

Temporal patterns in multi-modal social interaction between elderly users and service robot (2019)
Journal Article
Wang, N., Di Nuovo, A., Cangelosi, A., & Jones, R. (2019). Temporal patterns in multi-modal social interaction between elderly users and service robot. Interaction Studies, 20(1), 4-24. https://doi.org/10.1075/is.18042.wan

Social interaction, especially for older people living alone is a challenge currently facing human-robot interaction (HRI). There has been little research on user preference towards HRI interfaces. In this paper, we took both objective observations a... Read More about Temporal patterns in multi-modal social interaction between elderly users and service robot.

A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System (2019)
Journal Article
Luo, J., Liu, C., Wang, N., & Yang, C. (2019). A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System. IEEE Access, 7, 143912-143920. https://doi.org/10.1109/ACCESS.2019.2945674

© 2013 IEEE. Performance of teleoperation can be greatly influenced by time delay in the process of tele-manipulation with respect to accuracy and transparency. Wave variable is an effective algorithm to achieve a good stable capability. However, som... Read More about A Wave Variable Approach with Multiple Channel Architecture for Teleoperated System.

Exploration of muscle fatigue effects in bioinspired robot learning from sEMG signals (2018)
Journal Article
Wang, N., Xu, Y., Ma, H., & Liu, X. (2018). Exploration of muscle fatigue effects in bioinspired robot learning from sEMG signals. Complexity, 2018(49207), https://doi.org/10.1155/2018/4920750

© 2018 Ning Wang et al. To investigate the effects of muscle fatigue on bioinspired robot learning quality in teaching by demonstration (TbD) tasks, in this work, we propose to first identify the emerging muscle fatigue phenomenon of the human demons... Read More about Exploration of muscle fatigue effects in bioinspired robot learning from sEMG signals.

The multi-modal interface of Robot-Era multi-robot services tailored for the elderly (2017)
Journal Article
Di Nuovo, A., Broz, F., Wang, N., Belpaeme, T., Cangelosi, A., Jones, R., …Dario, P. (2018). The multi-modal interface of Robot-Era multi-robot services tailored for the elderly. Intelligent Service Robotics, 11(1), 109-126. https://doi.org/10.1007/s11370-017-0237-6

© 2017, The Author(s). Socially assistive robotic platforms are now a realistic option for the long-term care of ageing populations. Elderly users may benefit from many services provided by robots operating in different environments, such as providin... Read More about The multi-modal interface of Robot-Era multi-robot services tailored for the elderly.

A user-centric design of service robots speech interface for the elderly (2016)
Book Chapter
Wang, N., Broz, F., Di Nuovo, A., Belpaeme, T., & Cangelosi, A. A user-centric design of service robots speech interface for the elderly. In A. Esposito (Ed.), Recent Advances in Nonlinear Speech Processing (275-283). Springer International Publishing Switzerland

The elderly population in the Europe have quickly increased and will keep growing in the coming years. In facing the elder care challenges posed by the amount of seniors staying alone in their own homes, great efforts have been made to develop advanc... Read More about A user-centric design of service robots speech interface for the elderly.

A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation (2016)
Journal Article
Liang, P., Yang, C., Wang, N., & Li, R. (2016). A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation. Discrete Dynamics in Nature and Society, 2016(689703), https://doi.org/10.1155/2016/6897030

© 2016 Peidong Liang et al. We have developed a new discrete-time algorithm of stiffness extraction from muscle surface electromyography (sEMG) collected from human operator's arms and have applied it for antidisturbance control in robot teleoperatio... Read More about A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation.

Extracting and selecting distinctive EEG features for efficient epileptic seizure prediction (2014)
Journal Article
Wang, N., & Lyu, M. R. (2015). Extracting and selecting distinctive EEG features for efficient epileptic seizure prediction. IEEE Journal of Biomedical and Health Informatics, 19(5), 1648-1659. https://doi.org/10.1109/JBHI.2014.2358640

© 2013 IEEE. This paper presents compact yet comprehensive feature representations for the electroencephalogram (EEG) signal to achieve efficient epileptic seizure prediction performance. The initial EEG feature vectors are formed by acquiring the do... Read More about Extracting and selecting distinctive EEG features for efficient epileptic seizure prediction.

Robust speaker recognition using denoised vocal source and vocal tract features (2010)
Journal Article
Wang, N., Ching, P. C., Zheng, N., & Lee, T. (2011). Robust speaker recognition using denoised vocal source and vocal tract features. IEEE Transactions on Audio, Speech and Language Processing, 19(1), 196-205. https://doi.org/10.1109/TASL.2010.2045800

To alleviate the problem of severe degradation of speaker recognition performance under noisy environments because of inadequate and inaccurate speaker-discriminative information, a method of robust feature estimation that can capture both vocal sour... Read More about Robust speaker recognition using denoised vocal source and vocal tract features.