All Outputs (39)

MechTac: A multifunctional tendon-linked optical tactile sensor for in/out-the-field-of-view perception with deep learning (2023)
Conference Proceeding
Lu, Z., Yue, T., Zhao, Z., Si, W., Wang, N., & Yang, C. (2023). MechTac: A multifunctional tendon-linked optical tactile sensor for in/out-the-field-of-view perception with deep learning. In IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. https://doi.org/10.1109/iecon51785.2023.10311762

Tactile sensors can be used for motion detection and object perception in robot manipulation. The contact detection within the camera's visual inspection area has been well-developed, but perception outside the field of view of the camera is overlook... Read More about MechTac: A multifunctional tendon-linked optical tactile sensor for in/out-the-field-of-view perception with deep learning.

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.

Handheld device design for robotic teleoperation based on multi-sensor fusion (2023)
Conference Proceeding
Xie, L., Huang, D., Lu, Z., Wang, N., & Yang, C. (2023). Handheld device design for robotic teleoperation based on multi-sensor fusion. In 2023 IEEE International Conference on Mechatronics (ICM). https://doi.org/10.1109/ICM54990.2023.10102054

Precise leader-follower control is critical for teleop- eration. This paper designs and implements a low-cost leader device for unilateral teleoperation scenario. Monocular vision based on fiducial markers and MEMS Inertial Measurement Unit (IMU) are... Read More about Handheld device design for robotic teleoperation based on multi-sensor fusion.

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.

A multimodal teleoperation interface for human-robot collaboration (2023)
Conference Proceeding
Si, W., Zhong, T., Wang, N., & Yang, C. (2023). A multimodal teleoperation interface for human-robot collaboration. In 2023 IEEE International Conference on Mechatronics (ICM). https://doi.org/10.1109/ICM54990.2023.10102060

Human-robot collaboration provides an effective approach to combine human intelligence and the autonomy of robots, which can improve the safety and efficiency of the robot. However, developing an intuitive and immersive human-robot interface with mul... Read More about A multimodal teleoperation interface for human-robot collaboration.

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.

Human-in-the-loop Learning and Control for Robot Teleoperation (2023)
Book
Yang, C., Luo, J., & Wang, N. (2023). Human-in-the-loop Learning and Control for Robot Teleoperation. Elsevier. https://doi.org/10.1016/C2021-0-02620-1

Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning tech... Read More about Human-in-the-loop Learning and Control for Robot Teleoperation.

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.

A novel robot skill learning framework based on bilateral teleoperation (2022)
Conference Proceeding
Si, W., Yue, T., Guan, Y., Wang, N., & Yang, C. (2022). A novel robot skill learning framework based on bilateral teleoperation. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). https://doi.org/10.1109/case49997.2022.9926526

In this paper, a bilateral teleoperation-based robot skill learning framework is developed to transfer multi-step and contact manipulation skills from humans to robots. Robot skill acquisition via bilateral teleoperation provides a solution for human... Read More about A novel robot skill learning framework based on bilateral teleoperation.

Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance (2022)
Conference Proceeding
Huang, H., Lu, Z., Wang, N., & Yang, C. (2022). Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance. In 2022 27th International Conference on Automation and Computing (ICAC). https://doi.org/10.1109/ICAC55051.2022.9911082

A fixed-time adaptive neural network control scheme is designed for an unknown model manipulator system with input saturation and external environment disturbance, so that the system convergence time can be parameterized and not affected by the initi... Read More about Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance.

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.

A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use (2022)
Conference Proceeding
Lu, Z., Wang, N., Li, M., & Yang, C. (2022). A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use. . https://doi.org/10.1109/ICCA54724.2022.9831826

Dynamic Movement Primitives (DMPs) is a general method for learning skills from demonstrations. Most previous research on DMP has focused on point to point skill learning and training, and the skills learned are usually generalized based on the same... Read More about A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use.

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.