Dr Weiyong Si

Dr Weiyong Si

Dr Weiyong Si is a Lecturer at the University of Essex, specializing in robotics and AI, with a focus on robot learning, control, and human-robot interaction.

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Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. New position will be open To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

Robot-assisted medical examination

Tele-echography has emerged as a promising and effective solution, leveraging the expertise of sonographers and the autonomy of robots to perform ultrasound scanning for patients residing in remote areas, without the need for in-person visits by the sonographer. In this project, we develop a teleoperation system for robot-assisted sonography with two different interfaces, a haptic device-based interface and a low-cost 3D Mouse-based interface, which can achieve continuous and intuitive telemanipulation by a leader device with a small workspace.

An Perception Enhanced Human-robot Skill Transfer Method for Reactive Interaction

We propose a trust human-robot skill transfer framework, interpretive and reactive dynamic system (IRDS), by investigating the behaviour tree (BT) and dynamic movement primitives (DMPs) enhanced by the feedback from perceived information for dynamic and uncertain tasks and environments. Human sensorimotor control allows interactions with various environments and accomplishes complex manipulation tasks with uncertainty; however, it is still hard for robots to own this capability. In this work, we aim to transfer these reactive skills to robots, which enable robots to interact with humans and environments under varying uncertainty.

Soft Suction

Suction adhesion is widely used by natural creatures for gripping irregular objects (e.g., rocks), but their artificial counterparts show less adaptation in the same situation. In this work, we developed a contact-triggered suction cup with the ability to adapt to objects with complex and irregular shapes.

UAV landing on moving vehicle autonomously

In this project, we developed a vision-based UAV autonomous landing solution on a moving car. This project designed a new landing pad and its recognition algorithm to achieve relative pose estimation with high sampling rate. Utilization of monocular gimbaled camera expand the field of view and improves the reliability of identification as well. All above investigates solutions for the challenging problem of autonomous landing on a moving vehicle of multi-rotors Unmanned Aerial Vehicles.

Unified deep learning and control framework for robot-assisted sonography

In this work, we proposed a novel robot-assisted ultrasound scanning framework, integrating deep multimodal imitation learning and model-based compliant control. We investigated the deep imitation learning model to fuse multimodal information, including the RGB image, force profile, ultrasound image, and proprioceptive information for robot-assisted ultrasound scanning artery.

Waste Robot: Vision-based waste sorting system

Sorting wood waste from other waste streams using robotic systems involves the use of advanced technology and automation to efficiently separate wood materials from mixed waste. This project studied vision-based solution for waste sorting by Baxter robot arm.

Robot-assisted composite layup

In this work, 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-robot skill transfer, it is still difficult to transfer the manipulation skill to robots through teleoperation efficiently and intuitively. In this project, we developed an impedance-based control architecture of telemanipulation in task space for the human-robot skill transfer through teleoperation.

publications

Paper Title Number 1 SWY

Published in Journal 1, 2009

Guo, Peng, Weiyong Si, and Chenguang Yang. “A novel framework inspired by human behavior for peg-in-hole assembly.” Robotic Intelligence and Automation 44, no. 5 (2024): 713-723.

Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
Download Paper | Download Slides

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
Download Paper

talks

teaching

Robotics Foundation

Undergraduate course, University of the West of England, Bristol, School of Engineering, 2022

Associate Lecturer in Robotics and AI at the University of West of England, Bristol (UWE), UK. 2022

Advanced Embedded Systems Design (CE323)

Undergraduate course, University of Essex, School of Computer Science and Electronic Engineering (CSEE), 2023

Module leader for Advanced Embedded Systems Design (CE323)/(CE860) 2023