All Outputs (9)

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 novel robot skill learning framework based on bilateral teleoperation (2022)
Presentation / Conference Contribution

In this paper, a bilateral teleoperation-based robot skill learning framework is developed to transfer multi-step and contact manipulation skills from humans to robots. Robot skill acquisition via bilateral teleoperation provides a solution for human... Read More about A novel robot skill learning framework based on bilateral teleoperation.

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.

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.

Adaptive compliant skill learning for contact-rich manipulation with human in the loop (2022)
Journal Article

It is essential for the robot manipulator to adapt to unexpected events and dynamic environments while executing the physical contact-rich tasks. Although a range of methods have been investigated to enhance the adaptability and generalization capabi... Read More about Adaptive compliant skill learning for contact-rich manipulation with human in the loop.

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.

A framework for composite layup skill learning and generalizing through teleoperation (2022)
Journal Article

In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-rob... Read More about A framework for composite layup skill learning and generalizing through teleoperation.