Xinliang Guo
Contact information
Thesis title
Muscle Signal Based Interface for Responsive Physically-Assertive Robotics
Research overview
Physical Human-Robot Interaction (pHRI) is critical given its broad applications in healthcare and manufacturing. For safety and comfort reasons, pHRI systems are always expected to remain stable while the human operator interacts with the robot. This stability is classically guaranteed through force/velocity control strategies which are unfortunately conservative and sacrifice system performance to maintain stability. While human muscle activation based approaches were recently attempted to improve system performance while maintaining safe interaction, they have yet to be systematically developed and evaluated for pHRI. This project thus aims to develop and evaluate methodologies to improve performance while maintaining stability during pHRI.
Supervisors
Qualifications
M.Phil. Rehabilitation Engineering, Medical Robotics, The University of Melbourne, Australia (2023)
M.Eng. Electrical and Electronic Engineering, The University of Melbourne, Australia (2020)
B.Eng. Electrical Engineering, Central South University, China (2017)