All Outputs (6)

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.

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.

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.

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.

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.