Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Uchenna Ogenyi.


The work on this project will:

  • Conduct a detailed analysis of manipulation tasks involved in human-robot interaction. Decompose complex tasks into sub-skills and identify key elements that contribute to successful task completion.
  • Gather data through human demonstrations of manipulation tasks. Capture human movements, strategies, and decision-making processes to understand the nuances of skilled execution.
  • Develop a robust skill representation model that captures the essential features of both human and robot manipulative skills. This may involve the use of machine learning techniques to extract relevant patterns and features.
  • Implement learning algorithms that allow robots to learn manipulation skills from human demonstrations. Train the system to replicate human-like movements and decision-making in various scenarios.
  • Enhance the adaptability and generalization capabilities of the framework. Enable the robot to apply learned skills to new, unseen situations and adapt its behaviour based on changes in the environment or task requirements.


The human capability to achieve consistent sensorimotor coordination with the environment has opened avenues for developing robust control strategies. By leveraging this coordination, humans interact adeptly with the environment. Current efforts in robotics are aligning with these control strategies, envisioning a future where robots seamlessly integrate into society as occupants, helpers, and tools. The key challenge lies in facilitating joint work between humans and robots to attain common goals, involving simultaneous interaction with an unknown environment. This interaction introduces unpredictable parameters, making it challenging to differentiate between components related to human behaviour and those arising from environmental interaction.

Considering this challenge, the future trajectory in robotics emphasizes programming robots through demonstration. This approach enables the transfer of human primitive knowledge and intention to a robotic manipulator. The goal is to bridge the gap between human-robot collaboration, allowing robots to learn and execute tasks based on human guidance and expertise.

In summary, this project aims to create a robust and adaptive framework that allows robots to learn, execute, and adapt manipulation skills in collaboration with humans. The focus is on enhancing the synergy between humans and robots in various manipulation tasks, contributing to the advancement of human-robot interaction/collaboration in real-world scenarios.


Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Applicants should possess an understanding of the core principles in robotics, computer vision, and machine learning techniques. A good knowledge of Python/C++ programming, good analytical skills, and a foundation in computer science or related fields are essential requirements. The ideal candidate must demonstrate the ability to think critically and independently, including the formulation of research problems. Additionally, effective oral and written communication skills, along with proficient time management, are highly valued.


How to apply

We’d encourage you to contact Dr Uchenna Ogenyi ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: COMP6251025