All Outputs (10)

Multi-purpose tactile perception based on deep learning in a new tendon-driven optical tactile sensor (2022)
Presentation / Conference Contribution

In this paper, we create a new tendon-connected multi-functional optical tactile sensor, MechTac, for object perception in the field of view (TacTip) and location of touching points in the blind area of vision (TacSide). In a multi-point touch task,... Read More about Multi-purpose tactile perception based on deep learning in a new tendon-driven optical tactile sensor.

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.

A modified LSTM model for Chinese sign language recognition using leap motion (2022)
Presentation / Conference Contribution

At present, there are about 70 million deaf people using sign language in the world, but for most normal people, it is difficult to understand the meaning of the sign language expression. Therefore, it is of great importance to explore the ways of re... Read More about A modified LSTM model for Chinese sign language recognition using leap motion.

Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance (2022)
Presentation / Conference Contribution

A fixed-time adaptive neural network control scheme is designed for an unknown model manipulator system with input saturation and external environment disturbance, so that the system convergence time can be parameterized and not affected by the initi... Read More about Fixed-time adaptive neural control for robot manipulators with input saturation and disturbance.

Novel gripper-like exoskeleton design for robotic grasping based on learning from demonstration (2022)
Presentation / Conference Contribution

Learning from demonstration (LfD) has been developed and proved to be a promising method for transferring skill knowledge from human to robot. It is desired to have a demonstration device that can effectively map demonstrations to the robot's motion... Read More about Novel gripper-like exoskeleton design for robotic grasping based on learning from demonstration.

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.

A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use (2022)
Presentation / Conference Contribution

Dynamic Movement Primitives (DMPs) is a general method for learning skills from demonstrations. Most previous research on DMP has focused on point to point skill learning and training, and the skills learned are usually generalized based on the same... Read More about A novel dynamic movement primitives-based skill learning and transfer framework for multi-tool use.

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.