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Deep learning based human intention recognition in Human-Robot interaction

   School of Computing

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

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 Bangli Liu.

The work on this project will:

  • Definition of novel vision-based presentation of human intention
  • Identification and creation of human intention dataset in human-robot interaction environment
  • Development and application of deep learning techniques to predict human intentions

Project description

Autonomous robots are becoming part of modern society, and therefore, the development of autonomous robots that can function as productive members of human-robot teams becomes ever important. Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human–robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. To achieve effective interactions with humans, artificial robots must reason about the goals and intentions of humans. By observing the history of humans’ actions such as physical actions, robots can build a basis for recognising intentions and predicting future actions, which in turn shapes their interactions with humans. 

This project aims to develop vision based human intention recognition algorithms and their applications to human-robot interaction environment. Different deep learning models will be explored to achieve effective human intention prediction. In addition, the research will focus on exploring and designing a novel approach to develop a way to capture and link human’s behaviours (such as actions and visual attentions) to present human intentions. 

The supervisor Dr Bangli Liu has an extensive research experience in the field of human behaviour analysis, computer vision and Machine learning.

The successful candidate will have the chance to work on a cutting-edge research project and visit/work with different schools, which will be excellent opportunities for skills and career development.

General admissions criteria

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

You should have an experience of the fundamentals of Computer Vision, Data Analytics and Machine Learning techniques. Competent in applying Opencv and deep learning platforms (Tensorflow or Pytorch). 

Good programming skills in Python and analytical skills, knowledge of foundations of computer science are also required. The applicant should be able to think independently, including the formulation of research problems and have strong oral and written communication skills and good time management.

How to Apply

We encourage you to contact Dr Bangli Liu () to discuss your interest before you apply, quoting the project code below.

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:COMP5821023

Funding Notes

Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK students only).

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