PhD Study : RECASE: Robot-Enabled Care system in Smart Environments

Summary

Background: Smart environments have been developed for daily activity monitoring to support independent living over the past decade. The rapid development of sensor technology and IOT has brought smart environments into daily life, especially in supporting home care. Recent years have seen the rising of robots and AI and their applications at home to provide service and care. While these have drawn attentions from the research community, it remains challenge to develop a more intelligent and autonomous system to support independent living at home.

Aim: The proposal aims to develop a robot-enabled care system in smart environments to support elderly people living at home independently. The project will enable robot communicates with IOT sensors and wearable sensors in the smart environment to monitor daily activity patterns, aid daily activities, and prevent risks such as falls. The project will extend existing projects on robot indoor navigation and situational reasoning with focus on multi-agent control, data fusion and integrative reasoning.

Methodology: A ROS-based re-programmable robot will be used in the study. Sensors in the smart environments will include IOT sensors and wearable sensors such as PRIs, cameras, switches, microphones, activity wrist bands and blood pressure monitors. The RECASE robot will take integrated readings from the sensors and apply machine learning algorithms to detect events and activities. Based on multi-agent based reasoning, the robot will make decisions to support the user living at home. Multi-agent approaches with Bayesian analysis and knowledge-based reasoning algorithms will be developed. Coaching will be the main role of the proposed RECASE robot.

Outcome: The expected outcome and impact of this project will be a set of robust machine learning and reasoning algorithms for the RECASE care robot system. The project aligns with the research strategy of data analytics and connected health in Pervasive Computing Research Group and Computer Science Research Unit. High quality of research papers will be expected from the project and this PhD project will provide preliminary study leading to a RCUK research proposal on care robots.

References:

Khosla, R., Nguyen, K., & Chu, M. T. (2016). Socially assistive robot enabled personalised care for people with dementia in Australian private homes.

Wilson, G., Pereyda, C., Raghunath, N., de la Cruz, G., Goel, S., Nesaei, S., ... & Cook, D. J. (2019). Robot-enabled support of daily activities in smart home environments. Cognitive Systems Research, 54, 258-272.

Hesse, S., Tomelleri, C., Bardeleben, A., Werner, C., & Waldner, A. (2012). Robot-assisted practice of gait and stair climbing in nonambulatory stroke patients. J Rehabil Res Dev, 49(4), 613-622.

Goel, S. (2019, August). Teaching robots to interact with humans in a smart environment. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (pp. 6434-6435). AAAI Press.

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.

• Sound understanding of subject area as evidenced by a comprehensive research proposal

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.

• Publications record appropriate to career stage
• A comprehensive and articulate personal statement
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

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