All Outputs (31)

A bio-inspired multi-functional tendon-driven tactile sensor and application in obstacle avoidance using reinforcement learning (2023)
Journal Article
Lu, Z., Zhao, Z., Yue, T., Zhu, X., & Wang, N. (2024). A bio-inspired multi-functional tendon-driven tactile sensor and application in obstacle avoidance using reinforcement learning. IEEE Transactions on Cognitive and Developmental Systems, 16(2), 407 - 415. https://doi.org/10.1109/tcds.2023.3297361

This paper presents a new bio-inspired tactile sensor that is multi-functional and has different sensitivity contact areas. The TacTop area is sensitive and is used for object classification when there is a direct contact. On the other hand, the TacS... Read More about A bio-inspired multi-functional tendon-driven tactile sensor and application in obstacle avoidance using reinforcement learning.

Distributed observer-based prescribed performance control for multi-robot deformable object cooperative teleoperation (2023)
Journal Article
Lu, Z., Wang, N., Si, W., & Yang, C. (in press). Distributed observer-based prescribed performance control for multi-robot deformable object cooperative teleoperation. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2023.3292553

In this paper, a distributed observer-based prescribed performance control method is proposed for using a multi-robot teleoperation system to manipulate a common deformable object. To achieve a stable position-tracking effect and realize the desired... Read More about Distributed observer-based prescribed performance control for multi-robot deformable object cooperative teleoperation.

A multimodal human-robot sign language interaction framework applied in social robots (2023)
Journal Article
Li, J., Zhong, J., & Wang, N. (2023). A multimodal human-robot sign language interaction framework applied in social robots. Frontiers in Neuroscience, 17, Article 1168888. https://doi.org/10.3389/fnins.2023.1168888

Deaf-mutes face many difficulties in daily interactions with hearing people through spoken language. Sign language is an important way of expression and communication for deaf-mutes. Therefore, breaking the communication barrier between the deaf-mute... Read More about A multimodal human-robot sign language interaction framework applied in social robots.

Review on human-like robot manipulation using dexterous hands (2023)
Journal Article
Kadalagere Sampath, S., Wang, N., Wu, H., & Yang, C. (2023). Review on human-like robot manipulation using dexterous hands. Cognitive Computation and Systems, 5(1), 14-29. https://doi.org/10.1049/ccs2.12073

In recent years, human hand-based robotic hands or dexterous hands have gained attention due to their enormous capabilities of handling soft materials compared to traditional grippers. Back in the earlier days, the development of a hand model close t... Read More about Review on human-like robot manipulation using dexterous hands.

A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control (2022)
Journal Article
Lu, Z., Wang, N., Li, Q., & Yang, C. (2023). A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control. Neurocomputing, 521, 146-159. https://doi.org/10.1016/j.neucom.2022.11.076

Due to changes in the environment and errors that occurred during skill initialization, the robot's operational skills should be modified to adapt to new tasks. As such, skills learned by the methods with fixed features, such as the classical Dynamic... Read More about A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control.

A robotic learning and generalization framework for curved surface based on modified DMP (2022)
Journal Article
Xue, X., Dong, J., Lu, Z., & Wang, N. (2023). A robotic learning and generalization framework for curved surface based on modified DMP. Robotics and Autonomous Systems, 160, 104323. https://doi.org/10.1016/j.robot.2022.104323

How to reproduce and generalize the skills acquired by demonstrating is a hot topic for researchers. (1) A compliant continuous drag demonstration system based on discrete admittance model was designed to continuously and smoothly drag or demonstrate... Read More about A robotic learning and generalization framework for curved surface based on modified DMP.

Biomimetic force and impedance adaptation based on broad learning system in stable and unstable tasks: Creating an incremental and explainable neural network with functional linkage (2022)
Journal Article
Lu, Z., & Wang, N. (in press). Biomimetic force and impedance adaptation based on broad learning system in stable and unstable tasks: Creating an incremental and explainable neural network with functional linkage. IEEE Robotics and Automation Magazine, 2-13. https://doi.org/10.1109/MRA.2022.3188218

This article presents a novel biomimetic force and impedance adaption framework based on the broad learning system (BLS) for robot control in stable and unstable environments. Different from iterative learning control, the adaptation process is real... Read More about Biomimetic force and impedance adaptation based on broad learning system in stable and unstable tasks: Creating an incremental and explainable neural network with functional linkage.

Adaptive compliant skill learning for contact-rich manipulation with human in the loop (2022)
Journal Article
Si, W., Guan, Y., & Wang, N. (2022). Adaptive compliant skill learning for contact-rich manipulation with human in the loop. IEEE Robotics and Automation Letters, 7(3), 5834 - 5841. https://doi.org/10.1109/LRA.2022.3159163

It is essential for the robot manipulator to adapt to unexpected events and dynamic environments while executing the physical contact-rich tasks. Although a range of methods have been investigated to enhance the adaptability and generalization capabi... Read More about Adaptive compliant skill learning for contact-rich manipulation with human in the loop.

An adaptive fuzzy control for human-in-the-loop operations with varying communication time delays (2022)
Journal Article
Lu, Z., Guan, Y., & Wang, N. (2022). An adaptive fuzzy control for human-in-the-loop operations with varying communication time delays. IEEE Robotics and Automation Letters, 7(2), 5599-5606. https://doi.org/10.1109/LRA.2022.3158540

Time delay, especially varying time delay, is always an important factor affecting the stability to the human-in-the-loop system. Previous research usually focuses on the performance of the internal signal transmission part, but rarely considers the... Read More about An adaptive fuzzy control for human-in-the-loop operations with varying communication time delays.

A framework for composite layup skill learning and generalizing through teleoperation (2022)
Journal Article
Si, W., Wang, N., Li, Q., & Yang, C. (2022). A framework for composite layup skill learning and generalizing through teleoperation. Frontiers in Neurorobotics, 16, Article 840240. https://doi.org/10.3389/fnbot.2022.840240

In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-rob... Read More about A framework for composite layup skill learning and generalizing through teleoperation.

Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system (2021)
Journal Article
Lu, Z., Wang, N., Li, M., & Yang, C. (2022). Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system. IEEE Transactions on Fuzzy Systems, 30(6), 1506-1515. https://doi.org/10.1109/tfuzz.2021.3136933

Different from previous work on single skill learning from human demonstrations, an incremental motor skill learning, generalization and control method based on dynamic movement primitives (DMP) and broad learning system (BLS) is proposed for extract... Read More about Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system.

A unified parametric representation for robotic compliant skills with adaptation of impedance and force (2021)
Journal Article
Zeng, C., Li, Y., Guo, J., Huang, Z., Wang, N., & Yang, C. (2022). A unified parametric representation for robotic compliant skills with adaptation of impedance and force. IEEE/ASME Transactions on Mechatronics, 27(2), 623-633. https://doi.org/10.1109/tmech.2021.3109160

Robotic compliant manipulation is a very challenging but urgent research spot in the domain of robotics. One difficulty lies in the lack of a unified representation for encoding and learning of compliant profiles. This article aims to introduce a nov... Read More about A unified parametric representation for robotic compliant skills with adaptation of impedance and force.

An improvement of robot stiffness-adaptive skill primitive generalization using the surface electromyography in human–robot collaboration (2021)
Journal Article
Guan, Y., Wang, N., & Yang, C. (2021). An improvement of robot stiffness-adaptive skill primitive generalization using the surface electromyography in human–robot collaboration. Frontiers in Neuroscience, 15, Article 694914. https://doi.org/10.3389/fnins.2021.694914

Learning from Demonstration in robotics has proved its efficiency in robot skill learning. The generalization goals of most skill expression models in real scenarios are specified by humans or associated with other perceptual data. Our proposed frame... Read More about An improvement of robot stiffness-adaptive skill primitive generalization using the surface electromyography in human–robot collaboration.

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.