Skip to main content

Research Repository

Advanced Search

All Outputs (7)

A novel robust imitation learning framework for dual-arm object-moving tasks (2024)
Journal Article
Wang, W., Zeng, C., Lu, Z., & Yang, C. (in press). A novel robust imitation learning framework for dual-arm object-moving tasks. IEEE Transactions on Industrial Electronics, 1-9. https://doi.org/10.1109/tie.2024.3387098

Drawing inspiration from the mechanism of human skill acquisition, imitation learning has demonstrated remarkable performance. Over recent years, modelbased imitation learning combined with machine learning and control theory has been continuously de... Read More about A novel robust imitation learning framework for dual-arm object-moving tasks.

BioTacTip: A soft biomimetic optical tactile sensor for efficient 3D contact localization and 3D force estimation (2024)
Journal Article
Li, H., Nam, S., Lu, Z., Yang, C., Psomopoulou, E., & Lepora, N. F. (2024). BioTacTip: A soft biomimetic optical tactile sensor for efficient 3D contact localization and 3D force estimation. IEEE Robotics and Automation Letters, 9(6), 5314-5321. https://doi.org/10.1109/lra.2024.3387111

In this letter, we introduce a new soft biomimetic optical tactile sensor based on mimicking the interlocking structure of the epidermal-dermal boundary: the BioTacTip. The primary sensing unit comprises a sharp white tip surrounded by four black cov... Read More about BioTacTip: A soft biomimetic optical tactile sensor for efficient 3D contact localization and 3D force estimation.

A dynamic movement primitives-based tool use skill learning and transfer framework for robot manipulation (2024)
Journal Article
Lu, Z., Wang, N., & Yang, C. (in press). A dynamic movement primitives-based tool use skill learning and transfer framework for robot manipulation. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2024.3370139

This paper presents a framework for learning and transferring robot tool-use skills based on Dynamic Movement Primitives (DMPs) for robot fine manipulation. DMPs and their enhanced methods are employed to acquire a specific tool-use skill applicable... Read More about A dynamic movement primitives-based tool use skill learning and transfer framework for robot manipulation.

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.

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.

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.