PhD Study : CareBot: A Deep Learning based Multimodal Social Interaction Robot for Elderly Care

Summary

Due to the ongoing healthcare crisis and staff shortages, alternative forms of providing assistance to an ageing population is becoming critical to support a depleted healthcare community. Social robots have the potential to support this community by completing some day-to-day tasks in domestic environments, including non-contact measurement of vital signs; assessment of mood and keeping track medication schedules. This would free caregivers to focus on more acute situations. The ability to successfully communicate and interact with each other in a seamless manner is integral to the cohabitation of humans and robots. Sociable robots should be capable of proactively engaging with people within accepted social norms to enhance the interaction process. These social norms exist between humans as a combination of pre-defined ‘rules’ and through reinforcement learning from other humans. Currently, this paradigm is one in which robots struggle with, specifically in recognising many of the paralinguistic (e.g. tone, nuance) and non-verbal (e.g. body language) cues of humans.

This project aims to address the aforementioned shortcoming, by developing sociable robots (using a Pepper robot) that will utilise Multimodal deep learning techniques to socially interact with humans in a more meaningful manner.

The objective is to develop a computational model for human-robot social interaction using paralinguistic and non-verbal cues. Using robotic sensory information, these cues will be identified by extracting key features associated with each cue. A dataset of paralinguistic and non-verbal cues will be developed as part of this phase of the project which can be disseminated and utilised by the wider research community. A multimodal deep learning computational model will then be developed to analyse the extracted features for identification and classification of various paralinguistic and non-verbal social cues so that appropriate onward action can be executed. Endowing robots with the ability to conduct human-robot social interactions will contribute to advancing the integration of robot systems in human-centric environments.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• A comprehensive and articulate personal statement

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• For VCRS Awards, Masters at 75%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living