A Novel Framework for Robot Training and Tutoring using natural language
PhDs and postgraduate research
Self-funded PhD students only
School of Computing
October and February
Applications accepted all year round
Applications are invited for a self-funded, 3-years full-time or 6-years part-time PhD project, to commence in October 2020 or February 2021.
Given the advances in robotics and AI, most commercially available robots have been meticulously pre-programmed and trained for the predefined tasks. Such robots can out-perform human in environments where the tasks and work-spaces can be fully controlled and modelled as in the case of industrial applications. In less controlled and hazardous environments, expert operators have to be involved in the control loop to compensate for the inadequate abilities of robots in perceiving, understanding and assessing the surrounding environment and in planning the operations tasks.
Without a breakthrough in AI, this reliance on human operators is unlike to change in the near future, which severely limited the use autonomous robots in hazardous and domestic environments such as underwater rescue, firefighting and healthcare even if the hardware platforms are adequate.
In this project, we aim at a novel approach to enable robots to learn and understand their surround environments and to be tutored to perform diversified tasks by non-expert users using natural language.
By relaxing the stringent requirements on robot perception system and by relieving the demands for the specialised knowledge and skills of robot training, it is anticipated that the work would make it possible to deploy dexterous robots with higher accessibility and at lower costs for domestic and hazardous applications where both task operations and environments are varying and cannot be fully pre-defined.
The research will be based upon and extend our work on robot task and work-space analysis through grounding the spatial relationships and quantifiers in natural language. The work will involve natural language analysis, machine learning, knowledge modelling, intelligent robot control and task scheduling. Candidates with an interest in AI and robotics and a good undergraduate or master’s degree in computer science, engineering, or other relevant subject areas are invited to apply.
Fees and funding
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).
2020/2021 entry (for October 2020 and February 2021 entries)
Home/EU/CI full-time students: £4,407 p/a
Home/EU/CI part-time students: £2,204 p/a
International full-time students: £16,400 p/a
International part-time students: £8,200 p/a
PhD by Publication
External candidates £4,407 p/a
Members of staff £1,680 p/a*
2021/2022 entry (for October 2021 and February 2022 entries)
PhD and MPhil
Home/EU/CI full-time students: £4,407 p/a*
Home/EU/CI part-time students: £2,204 p/a*
International full-time students: £17,600 p/a
International part-time students: £8,800 p/a
All fees are subject to annual increase.
PhD by Publication
External Candidates £4,407 p/a*
Members of Staff £1,720 p/a*
If you are an EU student starting a programme in 2021/22 please visit this page.
*This is the 2020/21 UK Research and Innovation (UKRI) maximum studentship fee; this fee will increase to the 2021/22 UKRI maximum studentship fee when UKRI announces this rate in Spring 2021.
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.
You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an Civil Engineering or related area. 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
We welcome candidates with an interest in AI and robotics along with a good undergraduate or master’s degree in computer science, engineering, or other relevant subject areas.
How to apply
We’d encourage you to contact Dr Jiacheng Tan to discuss your interest before you apply, quoting the project code CCTS4520219.
When you are ready to apply, you can use our online application form and select ‘Computing and Creative Technologies’ as the subject area. 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.