Dr Weiyong Si
-
Email
w.si@essex.ac.uk -
Location
4B.524, Colchester Campus
-
Academic support hours
During Autumn Term my Academic Support Hours are 10:00-11:00 on Tuesdays or 14:00-15:00 on Fridays. I will be in my office, 4B.524. I can also meet on zoom by request at these times (I will check email during these support hours and respond with a link).
Profile
Biography
Dr Weiyong Si is a Lecturer (Assistant Professor) at the School of Computer Science and Electronic Engineering, University of Essex. He previously worked as a Research Assistant and Associate Lecturer with the School of Engineering, University of the West of England, affiliated with the Bristol Robotics Lab, and received Ph.D degree in Robotics and Machine Learning. He has been working on robot learning, robot control, teleoperation, machine vision, and guidance and navigation of autonomous systems. His research interest lies in the insection between AI and robotics. He currently focuses on robot learning and control, human-robot collaboration, mobile manipulation, and its applications in manufacturing, healthcare, and agriculture. He is a member of the Robotics Group. He is an IEEE Member and reviewer for several top journals and conferences including, IEEE Transactions on Robotics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Automation Science and Engineering, ICRA, IROS etc. He is the co-organising chair and special session chair for 25th IEEE International Conference on Industrial Technology (ICIT), the local organising Committee of 27th International Conference on Automation and Computing (ICAC), and the session chair for ICRA2024. He is a guest editor for a special issue of Frontiers in Robotics and AI focused on exploring the integration of Large Language Models (LLMs) and Computational Intelligence (CI) techniques to enhance advanced robotic systems. Dr Weiyong Si has a strong background in robotics and AI. He has practical project experience in intelligent control, machine learning, learning from demonstration, multimodal perception, planning and navigation of intelligent robots. He has led several practical projects, such as robot-assisted medical examination, flexible manufacturing and the navigation and guidance of autonomous UAVs. Please visit my Github page (https://siweiyong.github.io/) for more information about current research projects. If you are interested in his research, please feel free to reach out to him by email.
Qualifications
-
PhD University of the West of England, Bristol, (2023)
-
MSc Beijing Institute of Technology, (2018)
Appointments
University of Essex
-
Lecturer, School of Computer Science and Electronic Engineering (9/2023 - present)
Other academic
-
Reasearch Assistant, Bristol Robotics Laboratory (1/2020 - 9/2023)
-
Associate Lecturer, University of the West of England (9/2022 - 5/2023)
Research and professional activities
Research interests
Immersive Robot Teleoperation using VR/AR/MR
Design intuitive and immersive teleoperation interfaces for remote robots by leveraging multimodal sensing and VR/AR/MR technologies. This project integrates human intelligence with the precision of robotic control, enhancing the effectiveness of remote operations.
Intelligent Robot
Study human-robot skill transfer and generalisation for contact-rich manipulation tasks, including medical examinations, manipulating deformable objects, and assembly in manufacturing. Investigate machine learning technologies, such as deep learning and reinforcement learning, and employ them in intelligent robots.
Human-centered robotics applications
Research in human-centered robotics aims to address the common challenges in assistive robots, industrial robots, and agricultural robots.
Machine learning
Study of artificial intelligence for intelligent robots, focusing on the integration of machine learning, machine vision, and robotics. This research applies state-of-the-art AI techniques to develop advanced intelligent robots, including robotic arms, mobile robots, and more.
Human-robot Interaction
Study the compliant control and human intention recognition for human-robot collaboration.
Embodied Intelligence
Embodied intelligence is an emerging topic in the context of large language models (LLMs) and intelligent robots, driving the evolution of robotic systems for physical interaction applications, particularly in contact-rich manipulation tasks. This project aims to advance robot manipulation skills for contact-rich tasks, such as healthcare and dexterous manipulation in extreme environments.
Teaching and supervision
Current teaching responsibilities
-
Advanced Embedded Systems Design (CE323)
-
Advanced Embedded Systems Design (CE860)
Publications
Journal articles (16)
Si, W., Wang, N. and Yang, C., (2024). Design and Quantitative Assessment of Teleoperation-Based Human–Robot Collaboration Method for Robot-Assisted Sonography. IEEE Transactions on Automation Science and Engineering, 1-11
Lu, Z., Si, W., Wang, N. and Yang, C., (2024). Dynamic Movement Primitives-Based Human Action Prediction and Shared Control for Bilateral Robot Teleoperation. IEEE Transactions on Industrial Electronics. 71 (12), 16654-16663
Luo, J., Zhang, C., Si, W., Jiang, Y., Yang, C. and Zeng, C., (2024). A Physical Human–Robot Interaction Framework for Trajectory Adaptation Based on Human Motion Prediction and Adaptive Impedance Control. IEEE Transactions on Automation Science and Engineering, 1-12
Guo, P., Si, W. and Yang, C., (2024). A novel framework inspired by human behavior for peg-in-hole assembly. Robotic Intelligence and Automation. 44 (5), 713-723
Yue, T., Si, W., Keller, A., Yang, C., Bloomfield-Gadêlha, H. and Rossiter, J., (2024). Bioinspired multiscale adaptive suction on complex dry surfaces enhanced by regulated water secretion.. Proceedings of the National Academy of Sciences of USA. 121 (16), e2314359121-
Jin, Z., Si, W., Liu, A., Zhang, W-A., Yu, L. and Yang, C., (2023). Learning a Flexible Neural Energy Function With a Unique Minimum for Globally Stable and Accurate Demonstration Learning. IEEE Transactions on Robotics. 39 (6), 4520-4538
Lu, Z., Wang, N., Si, W. and Yang, C., (2023). Distributed Observer-Based Prescribed Performance Control for Multi-Robot Deformable Object Cooperative Teleoperation. IEEE Transactions on Automation Science and Engineering. 21 (3), 4143-4154
Dong, J., Si, W. and Yang, C., (2023). A novel human-robot skill transfer method for contact-rich manipulation task. Robotic Intelligence and Automation. 43 (3), 327-337
Zhao, G., Zeng, C., Si, W. and Yang, C., (2023). A human‐robot collaboration method for uncertain surface scanning. CAAI Transactions on Intelligence Technology
Xing, X., Burdet, E., Si, W., Yang, C. and Li, Y., (2023). Impedance Learning for Human-Guided Robots in Contact With Unknown Environments. IEEE Transactions on Robotics. 39 (5), 3705-3721
Zhang, D., Si, W., Fan, W., Guan, Y. and Yang, C., (2022). From Teleoperation to Autonomous Robot-assisted Microsurgery: A Survey. Machine Intelligence Research. 19 (4), 288-306
Si, W., Wang, N., Li, Q. and Yang, C., (2022). A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation. Frontiers in Neurorobotics. 16, 840240-
Si, W., Guan, Y. and Wang, N., (2022). Adaptive Compliant Skill Learning for Contact-Rich Manipulation With Human in the Loop. IEEE Robotics and Automation Letters. 7 (3), 5834-5841
Yue, T., Si, W., Partridge, AJ., Yang, C., Conn, AT., Bloomfield-Gadelha, H. and Rossiter, J., (2022). A Contact-Triggered Adaptive Soft Suction Cup. IEEE Robotics and Automation Letters. 7 (2), 3600-3607
Si, W., Wang, N. and Yang, C., (2021). Composite dynamic movement primitives based on neural networks for human–robot skill transfer. Neural Computing and Applications. 35 (32), 23283-23293
Si, W., Wang, N. and Yang, C., (2021). A review on manipulation skill acquisition through teleoperation‐based learning from demonstration. Cognitive Computation and Systems. 3 (1), 1-16
Book chapters (1)
Si, W., Guo, C., Dong, J., Lu, Z. and Yang, C., (2023). Deformation-Aware Contact-Rich Manipulation Skills Learning and Compliant Control. In: Springer Proceedings in Advanced Robotics. Springer International Publishing. 90- 104. 9783031227301
Conferences (24)
Si, W., A Vision-based Target Localization Method for Robot-assisted Sonography
Guo, P., Si, W. and Yang, C., (2024). Robot Hand-eye Calibration Method Incorporating Filtering Techniques
Yang, B., She, H., Si, W., Xu, Z., Yao, L. and Yang, X., (2024). Conditional Trigger Model Predictive Control for Aerial Manipulation
Xu, Z., She, H., Si, W., Yang, B., Yao, L. and Yang, X., (2024). Lightweight of SiamCAR Network for UAV Single Target Track
Wang, Z., Shi, D., Yang, C., Si, W. and Li, Q., (2024). Autonomous Liver Ultrasound Examination Based on Imitation Learning and Stiffness Estimation
Hu, H., Shi, D., Yang, C., Si, W. and Li, Q., (2024). A Novel Shared Control Framework Based on Imitation Learning
Yao, L., She, H., Si, W., Zhou, H., Yang, B. and Xu, Z., (2024). Mobile-SPEEDNet: A Lightweight Network for Non-Cooperative Spacecraft Pose Estimation
Fan, W., Li, H., Si, W., Luo, S., Lepora, N. and Zhang, D., (2024). ViTacTip: Design and Verification of a Novel Biomimetic Physical Vision-Tactile Fusion Sensor
Lu, Z., Yang, J., Li, H., Li, Y., Si, W., Lepora, N. and Yang, C., (2024). TacShade: A New 3D-printed Soft Optical Tactile Sensor Based on Light, Shadow and Greyscale for Shape Reconstruction
Zhu, M., She, H., Si, W. and Li, C., (2024). Lightweight Imitation Learning Algorithm with Error Recovery for Human Direction Correction
Xu, T., She, H., Si, W. and Li, C., (2024). Trajectory Generation by Sparse Demonstration Learning and Minimum Snap-based Optimization
Guo, K., Zeng, C., Si, W., Wang, N. and Yang, C., (2024). Adaptive Stiffness Control of Series Elastic Actuator Manipulators Based on Dynamic System
Si, W., Jin, Z., Lu, Z., Wang, N. and Yang, C., (2024). A Stable Guidance Method for Teleoperation-based Robot Learning from Demonstration
Si, W., Zhong, T., Wang, N. and Yang, C., (2023). A multimodal teleoperation interface for human-robot collaboration
Si, W., (2023). Robot Learning from Multiple Demonstrations Based on Generalized Gaussian Mixture Model
(2023). Best Student Paper Award
Si, W., Guo, C., Wang, N., Yang, M., Harris, R. and Yang, C., (2023). A Unified Deep Imitation Learning and Control Framework for Robot-Assisted Sonography
Lu, Z., Yue, T., Zhao, Z., Si, W., Wang, N. and Yang, C., (2023). MechTac: A Multifunctional Tendon-Linked Optical Tactile Sensor for In/Out-the-Field-of-View Perception with Deep Learning
Li, X., Si, W. and Yang, C., (2022). An Observation Based Method for Human Robot Writing Skill Transfer
Si, W., Yue, T., Guan, Y., Wang, N. and Yang, C., (2022). A Novel Robot Skill Learning Framework Based on Bilateral Teleoperation
Si, W., Wang, N. and Yang, C., (2021). Reactive and constrained motion primitive merging and adaptation
Dong, J., Si, W. and Yang, C., (2021). A DMP-based Online Adaptive Stiffness Adjustment Method
Si, W., She, H. and Wang, Z., (2017). Fuzzy PID controller for UAV tracking moving target
Wang, Z., She, H. and Si, W., (2017). Autonomous landing of multi-rotors UAV with monocular gimbaled camera on moving vehicle
Grants and funding
2024
Innovate to Elevate Project (I2E) with FirstGrade Recycling to look at the robotic sorting of wood waste from other waste streams
Babergh and Mid Suffolk (Innovate to Elevate Programme)
Contact
Academic support hours:
During Autumn Term my Academic Support Hours are 10:00-11:00 on Tuesdays or 14:00-15:00 on Fridays. I will be in my office, 4B.524. I can also meet on zoom by request at these times (I will check email during these support hours and respond with a link).
