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Project 1.2: Cobots learning by demonstration

Lead researcher

Project based at

Lead Partner Organisation


Cobots learning digital twins

This project seeks novel solutions to the following challenges: 1) How a robot gains skills and knowledge through biomimicry digital twining with minimal human intervention; 2) How a robot can adapt to varying operational conditions of the same task; 3) How a robot can apply the same learning ability to learn different tasks as a human does.  The Project will investigate the theory and algorithms for task learning that will help retain the knowledge of skilled operators during autonomous or semi-autonomous operations, and robot digital twining the human via imaging system, force/tactile sensors and data fusion.

The Australian Cobotics Centre is looking for a highly motivated PhD student to join this interdisciplinary collaborative project based at Swinburne. The PhD student will work towards a cobot learning framework and methods that allow a collaborative robot to gain skills and knowledge via biomimicry learning digital twins, sensor data fusion and deep machine learning.

Skills & experience

Desired Background

  • Excellent communication skills
  • Robotics, computer science, or mechatronics
  • Strong background in mathematics
  • Manufacturing or¬†Digitalisation

Desired Skills

  • Programing in C++, Python or Matlab
  • Knowledge of Robotics Operating Systems (ROS)

Associated Researchers

XiaoQi Chen

Research Program Co-lead (Biomimic Cobots program)
Swinburne University of Technology
View Bio

Peter Corke

Associate Director (Research Training)
Queensland University of Technology
View Bio

Jochen Deuse

Associate Director (Industry Engagement)
University of Technology Sydney
View Bio