All Outputs (15)

VERGNet: Visual enhancement guided robotic grasp detection under low-light condition (2023)
Journal Article
Niu, M., Lu, Z., Chen, L., Yang, J., & Yang, C. (2023). VERGNet: Visual enhancement guided robotic grasp detection under low-light condition. IEEE Robotics and Automation Letters, 8(12), 8541-8548. https://doi.org/10.1109/lra.2023.3330664

Although existing grasp detection methods have achieved encouraging performance under well-light conditions, repetitive experiments have found that the detection performance would deteriorate drastically under low-light conditions. Although supplemen... Read More about VERGNet: Visual enhancement guided robotic grasp detection under low-light condition.

Learning a flexible neural energy function with a unique minimum for globally stable and accurate demonstration learning (2023)
Journal Article
Jin, Z., Si, W., Liu, A., Zhang, W. A., Yu, L., & Yang, C. (in press). Learning a flexible neural energy function with a unique minimum for globally stable and accurate demonstration learning. IEEE Transactions on Robotics, https://doi.org/10.1109/tro.2023.3303011

Learning a stable autonomous dynamic system (ADS) encoding human motion rules has been shown as an effective way for demonstration learning. However, the stability guarantee may sacrifice the demonstration learning accuracy. This article solves the i... Read More about Learning a flexible neural energy function with a unique minimum for globally stable and accurate demonstration 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.

Visual-tactile robot grasping based on human skill learning from demonstrations using a wearable parallel hand exoskeleton (2023)
Journal Article
Lu, Z., Chen, L., Dai, H., Li, H., Zhao, Z., Zheng, B., …Yang, C. (2023). Visual-tactile robot grasping based on human skill learning from demonstrations using a wearable parallel hand exoskeleton. IEEE Robotics and Automation Letters, 8(9), 5384-5391. https://doi.org/10.1109/lra.2023.3295296

The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable manner. This letter is to model human grasping skills and transfer the learned skills to robots to improve grasping quality and success rate. First, we... Read More about Visual-tactile robot grasping based on human skill learning from demonstrations using a wearable parallel hand exoskeleton.

Two-stage grasp detection method for robotics using point clouds and deep hierarchical feature learning network (2023)
Journal Article
Liu, X., Huang, C., Li, J., Wan, W., & Yang, C. (2024). Two-stage grasp detection method for robotics using point clouds and deep hierarchical feature learning network. IEEE Transactions on Cognitive and Developmental Systems, 16(2), 720 - 731. https://doi.org/10.1109/tcds.2023.3289987

When human beings see different objects, they can quickly make correct grasping strategies through brain decisions. However, grasp, as the first step of most manipulation tasks, is still an open issue in robotics. Although many detection methods have... Read More about Two-stage grasp detection method for robotics using point clouds and deep hierarchical feature learning network.

Impedance learning for human-guided robots in contact with unknown environments (2023)
Journal Article
Xing, X., Burdet, E., Si, W., Yang, C., & Li, Y. (2023). Impedance learning for human-guided robots in contact with unknown environments. IEEE Transactions on Robotics, 39(5), 3705 - 3721. https://doi.org/10.1109/tro.2023.3281483

Previous works have developed impedance control to increase safety and improve performance in contact tasks, where the robot is in physical interaction with either an environment or a human user. This article investigates impedance learning for a rob... Read More about Impedance learning for human-guided robots in contact with unknown environments.

A novel human-robot skill transfer method for contact-rich manipulation task (2023)
Journal Article
Dong, J., Si, W., & Yang, C. (2023). A novel human-robot skill transfer method for contact-rich manipulation task. Robotic Intelligence and Automation, 43(3), https://doi.org/10.1108/RIA-01-2023-0002

Purpose: The purpose of this paper is to enhance the robot’s ability to complete multi-step contact tasks in unknown or dynamic environments, as well as the generalization ability of the same task in different environments. Design/methodology/approac... Read More about A novel human-robot skill transfer method for contact-rich manipulation task.

Dynamic motion primitives-based trajectory learning for physical human-robot interaction force control (2023)
Journal Article
Xing, X., Maqsood, K., Zeng, C., Yang, C., Yuan, S., & Li, Y. (2024). Dynamic motion primitives-based trajectory learning for physical human-robot interaction force control. IEEE Transactions on Industrial Informatics, 20(2), 1675 - 1686. https://doi.org/10.1109/TII.2023.3280320

One promising function of interactive robots is to provide a specific interaction force to human users. For example, rehabilitation robots are expected to promote patients' recovery by interacting with them with a prescribed force. However, motion un... Read More about Dynamic motion primitives-based trajectory learning for physical human-robot interaction force control.

A human-robot collaboration method for uncertain surface scanning (2023)
Journal Article
Zhao, G., Zeng, C., Si, W., & Yang, C. (in press). A human-robot collaboration method for uncertain surface scanning. CAAI Transactions on Intelligence Technology, https://doi.org/10.1049/cit2.12227

Robots are increasingly expected to replace humans in many repetitive and high-precision tasks, of which surface scanning is a typical example. However, it is usually difficult for a robot to independently deal with a surface scanning task with uncer... Read More about A human-robot collaboration method for uncertain surface scanning.

Design and control of a novel bionic mantis shrimp robot (2023)
Journal Article
Chen, G., Xu, Y., Yang, C., Yang, X., Hu, H., Chai, X., & Wang, D. (2023). Design and control of a novel bionic mantis shrimp robot. IEEE/ASME Transactions on Mechatronics, 28(6), 3376 - 3385. https://doi.org/10.1109/TMECH.2023.3266778

This article presents the development of a novel bionic robot, which is inspired by agile and fast mantis shrimp in the ocean. The developed bionic mantis shrimp robot has ten rigid-flexible swimming feet (pleopods) for swimming propulsion and a rope... Read More about Design and control of a novel bionic mantis shrimp robot.

A constrained framework based on IBLF for robot learning with human supervision (2023)
Journal Article
Shi, D., Li, Q., Yang, C., & Lu, Z. (2023). A constrained framework based on IBLF for robot learning with human supervision. Robotica, 41(8), 2451-2463. https://doi.org/10.1017/S0263574723000462

Dynamical movement primitives (DMPs) method is a useful tool for efficient robotic skills learning from human demonstrations. However, the DMPs method should know the specified constraints of tasks in advance. One flexible solution is to introduce th... Read More about A constrained framework based on IBLF for robot learning with human supervision.

Distributed collaborative control of redundant robots under weight-unbalanced directed graphs (2023)
Journal Article
Zheng, X., Liu, M., Jin, L., & Yang, C. (2024). Distributed collaborative control of redundant robots under weight-unbalanced directed graphs. IEEE Transactions on Industrial Informatics, 20(1), 681 - 690. https://doi.org/10.1109/TII.2023.3268778

In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network topology perspective are in larger a... Read More about Distributed collaborative control of redundant robots under weight-unbalanced directed graphs.

The classification and new trends of shared control strategies in telerobotic systems: A survey (2023)
Journal Article
Li, G., Li, Q., Yang, C., Su, Y., Yuan, Z., & Wu, X. (2023). The classification and new trends of shared control strategies in telerobotic systems: A survey. IEEE Transactions on Haptics, 16(2), 118-133. https://doi.org/10.1109/TOH.2023.3253856

Shared control, which permits a human operator and an autonomous controller to share the control of a telerobotic system, can reduce the operator's workload and/or improve performances during the execution of tasks. Due to the great benefits of combi... Read More about The classification and new trends of shared control strategies in telerobotic systems: A survey.

Adaptive fuzzy prescribed-time connectivity-preserving consensus of stochastic nonstrict-feedback switched multiagent systems (2023)
Journal Article
Yi, J., Li, J., & Yang, C. (2023). Adaptive fuzzy prescribed-time connectivity-preserving consensus of stochastic nonstrict-feedback switched multiagent systems. IEEE Transactions on Fuzzy Systems, 31(10), 3346-3357. https://doi.org/10.1109/tfuzz.2023.3252601

An adaptive fuzzy prescribed-time connectivity-preserving consensus protocol is designed for a class of stochastic nonstrict-feedback multiagent systems, in which periodic disturbances, switched nonlinearities, input saturation, and limited communica... Read More about Adaptive fuzzy prescribed-time connectivity-preserving consensus of stochastic nonstrict-feedback switched multiagent systems.

A gripper-like exoskeleton design for robot grasping demonstration (2023)
Journal Article
Dai, H., Lu, Z., He, M., & Yang, C. (2023). A gripper-like exoskeleton design for robot grasping demonstration. Actuators, 12(1), 39. https://doi.org/10.3390/act12010039

Learning from demonstration (LfD) is a practical method for transferring skill knowledge from a human demonstrator to a robot. Several studies have shown the effectiveness of LfD in robotic grasping tasks to improve the success rate of grasping and t... Read More about A gripper-like exoskeleton design for robot grasping demonstration.