A Multi-Sensor Interface for 
Arc Welding Training Tasks

The aim of this project is to develop a mixed reality multi-sensor platform to improve the teaching and learning experience of arc welding tasks.

Active Deformable Structures for Reconfigurable Robots  

The aim of this project is to develop novel mechatronic structures with intrinsic compliance to control the motion of robots. This project is supported by the Belt and Road Scholarship (Research Postgraduate).

Robotics Meets Cosmetic Dermatology

The aim of this project is to develop a robot to automate the manipulation of instruments in aesthetic dermatology procedures. This project is supported by RODS under grants H-ZDBA and H-ZDBU.

Thermal Servoing Controls and Sensing Systems

The aim of this project is to develop new perceptual and manipulation capabilities for temperature critical applications. This project is supported by the Jiangsu Industrial Technology Research Institute.

Point Cloud Based Surface Defect Inspection

The objective of this project is to develop a motion planning algorithm to automatically manipulate a line scanner over the surface of an object to detect defects. This work is a collaboration between PolyU and ASTRI.

Robotic US Imaging

for Scoliosis Assessment

This project aims to develop a force and image-guided system for manipulating an ultrasound probe along a spine so as to reconstruct its 3D structure. It is conducted in collaboration with Prof Zheng YP from the BME Department of PolyU.

Sensor-Guided Methods

for Robotic Arc Welding 

In this project, we are developing adaptive perceptual algorithms for automating welding tasks with robot manipulators. Funding source: Chinese National Engineering Research Centre for Steel Construction (CNERC) under grant BBV8.

Vison-Based Shape Control of Deformable Objects

The purpose of this project is to develop sensor-based methods for deforming soft objects into desired shapes with robot manipulators. Funding source: RGC General Research Fund 142039/17E 2018–2021, and the RGC-DAAD grant G-PolyU507/18.

Neuro-Inspired Sensorimotor Models for Autonomous Robots

We are developing neuro-inspired methods for computing sensorimotor models of robotic systems. This work is done in collaboration DTU Denmark and supported by the France/HK Joint Research Scheme under grant F-PolyU503/18, and by PolyU under grants 4-ZZHJ and G-YBYT.