All Outputs (6)

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.

Editorial: Sensing and control for efficient human-robot collaboration (2024)
Journal Article

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.