Advanced Proprioception for Robotic Legs

About the Project

Humans are complex mechanical systems of interconnected bodies with a high degree of freedom (DOF). Our inner structures/bodies have naturally evolved with advanced proprioception and control, enabling us to perform a wide range of actions/movements, such as running, walking, sitting, and jumping. In a bionic leg system—a bioinspired design of the human leg—proprioception is a critical component. It must not only be soft and flexible but also designed effectively to measure the complex movements of joints like the knee and ankle.

In this project, you will explore novel sensor design techniques that enable the measurement of complex motions in a robotic leg that mimics human biomechanics. The project will begin by studying the neuromusculoskeletal biomechanics of the human lower limbs, which will inspire the development of advanced multi-modal proprioception for a robotic lower limb (i.e., a robotic leg). You will work on designing flexible proprioceptive components, testing their performance, and validating their multi-modal or advanced proprioceptive capabilities.

This technology will ultimately be integrated into a robotic leg system using a data acquisition system to handle and process sensory data effectively. You will also apply advanced machine learning techniques to decouple and predict joint movements, which will serve as input for the robotic leg control system, located at the University of York. The final goal is to integrate proprioception into the closed-loop control of the robotic leg, enabling advanced movements and adaptability like human motion.

Additionally, you will become part of the Robotics and Movement Science communities at the University of York, where academics are engaged in a diverse range of cutting-edge robotics research.

About Movement Science and Engineering at York

Movement Science and Engineering is a subgroup within Healthcare Engineering at the University of York. Our team comprises 10 academics focused on research that aims to understand movement science and restore mobility to patients. Our research topics span a diverse range of expertise, from the development of MEMS sensors for studying proteins to AI-based signal analysis for the automated assessment of neurodegenerative and musculoskeletal (MSK) conditions and human-machine interactions with assistive robotics.

This project is open-ended making it suitable for MSc by Research and PhD level.

Entry requirements:

Candidates should have (or expect to obtain) a minimum of a UK upper second-class honors degree (2.1) or equivalent in Mechanical or Electrical Engineering. Experience in biomechanics or computer science will also be considered, however, you must show an understanding of fundamental principles of experimental robotics (mechanics, dynamics and control, signal processing etc).

Requirements:

• A background in engineering including electronic, electrical, mechanical, aerospace engineering, mechatronics and other related subjects.
• Programming skills in C/C++ and Python is a plus.
• Any experience or background in robotics is a plus but not a requirement.

If you have any questions about this position, please contact Dr. Babar Jamil, email: babar.jamil@york.ac.uk, and or Dr. Peter Ellison, email: peter.ellison@york.ac.uk.

How to apply:

Applicants must apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process. To apply, please select the PhD in Electronic Engineering. Please specify in your PhD application that you would like to be considered for this studentship and also select supervisors.

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the School of Physics, Engineering and Technology website for details about funding opportunities at York.