Dexterous Manipulation for Hybrid Robots Using Reinforcement Learning

About the Project

Hybrid Robotic manipulators combine soft and rigid components that allow them to be safer and more reliable than their rigid counterparts during their interactions with the world. This has significant potential in applications requiring dexterity and safety when working around humans, especially in a cluttered environment. Despite the current development in the control of these robots, there remains significant potential and challenges to overcome challenges in precise control during different dexterous interactions, this dexterity is important to enable them to have a range of manipulation capabilities to make them capable of completing a range of tasks. This project looks towards the design, development and implementation of reinforcement learning-based control methods for these robots to enable them to interact with objects.

This project will cover the following:

1. Developing simulation environments for hybrid robotic arm
2. Design and implementation of machine learning-based manipulation strategies
3. Testing and evaluation of autonomous dexterous manipulation for hybrid robots
4. Implementing human-robot collaboration and object handling and manipulation.

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.
• Simulation using Python/MATLAB.
• Machine learning background is desired.
• Any experience or background in robotics is a plus.

If you have any questions about this position, please contact Dr. Babar Jamil, email: babar.jamil@york.ac.uk.

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

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 project 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.