All Outputs (21)

Dynamic movement primitives-based human action prediction and shared control for bilateral robot teleoperation (2024)
Journal Article

This article presents a novel shared-control teleoperation framework that integrates imitation learning and bilateral control to achieve system stability based on a new dynamic movement primitives (DMPs) observer. First, a DMPs-based observer is firs... Read More about Dynamic movement primitives-based human action prediction and shared control for bilateral robot teleoperation.

A novel robust imitation learning framework for dual-arm object-moving tasks (2024)
Journal Article

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

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

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.

Tactile-based grasping stability prediction based on human grasp demonstration for robot manipulation (2024)
Journal Article

To minimize irrelevant and redundant information in tactile data and harness the dexterity of human hands. In this paper, we introduce a novel binary classification network with normalized differential convolution (NDConv) layers. Our method leverage... Read More about Tactile-based grasping stability prediction based on human grasp demonstration for robot manipulation.

VERGNet: Visual enhancement guided robotic grasp detection under low-light condition (2023)
Journal Article

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

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

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

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

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

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.

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

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

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

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.

Robust output-feedback predictive control for proximity eddy current de-tumbling with constraints and uncertainty (2022)
Journal Article

Proximity operation can significantly improve the efficiency of eddy current de-tumbling. However, the tumbling motion and non-cooperation of space debris make the chaser execute collision avoidance maneuvers and be influenced by model uncertainty. I... Read More about Robust output-feedback predictive control for proximity eddy current de-tumbling with constraints and uncertainty.

An adaptive fuzzy control for human-in-the-loop operations with varying communication time delays (2022)
Journal Article

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.

Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system (2021)
Journal Article

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.

DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation (2021)
Journal Article

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

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.

Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance (2021)
Journal Article

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.