RAL: Robotics for Assistive Living

Apply and key information  

This project is funded by:

    • Department for the Economy (DfE)
    • Vice Chancellor's Research Scholarship (VCRS)

Summary

The Cognitive Robotics team in the ISRC focuses on novel, advanced control methods for autonomous mobile robots, merging approaches from Artificial Intelligence, Cognitive Science and Engineering. Research in Cognitive Robotics at the ISRC ranges from investigating robotics as a science, to applications of robotics such as industrial robotics, robotics for assistive living and computer vision.

The Cognitive Robotics Laboratory in the ISRC is well equipped, possessing a wide range of robots; such as Shadow-Robot Dexterous Hand, 2x Robotnik Summit XL, 2x Pepper Humanoid Robots, a range of Kuka manipulator arms as well as vision systems permitting the capture of 2D and 3D visual data (Microsoft Kinect, Dynamic Vision Sensor), Vicon tracking system and high performance computing facilities.

This project builds upon the ISRC's research expertise in assistive robotics, focusing on developing intelligent systems that can adapt to and support individual user needs. The research encompasses several key areas of investigation:

* Human-Robot Interaction: Communication between users and robotic systems, considering factors such as user preferences, capabilities, and comfort levels.
* Robot Perception: Advanced sensing and interpretation of the environment and human activities, enabling robots to understand and respond appropriately to user needs and environmental contexts.
* Adaptive Learning and Cognition: Implementation of machine/deep learning approaches that allow robotic systems to personalise their assistance based on individual user patterns, preferences, and requirements.

Potential application domains include Assistive robotic manipulators; Smart Home environments; Healthcare companions; Tele-Healthcare and Human Activity Recognition.

As a new member of the Robotics team, the successful candidate will be supported by a large network of academic staff, research staff and fellow students with various areas of expertise, including access to multi-disciplinary research teams within the Intelligent Systems Research Centre. The PhD opportunity will provide the candidate with the skills necessary to become a leading expert in the state-of-the-art of assistive robotics.

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 demonstrable interest in the research area associated with the studentship

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

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

  • Department for the Economy (DfE)
  • Vice Chancellor's Research Scholarship (VCRS)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.

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.

Recommended reading

1. Bao, Y., Gong, W. & Yang, K. 2023, 'A Literature Review of Human–AI Synergy in Decision Making: From the Perspective of Affordance Actualization Theory', Systems, vol. 11, no. 9, p. 442.

2. Chen, K., Zhang, D., Yao, L., Guo, B., Yu, Z. & Liu, Y. 2021, 'Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges, and Opportunities', ACM Computing Surveys, vol. 54, no. 4, article 77.

3. Guemghar, I., Pires de Oliveira Padilha, P., Abdel-Baki, A., Jutras-Aswad, D., Paquette, J. & Pomey, M. 2022, 'Social Robot Interventions in Mental Health Care and Their Outcomes, Barriers, and Facilitators: Scoping Review', JMIR Mental Health, vol. 9, no. 4, e36094.

4. Raj, R. & Kos, A. 2024, 'Study of Human–Robot Interactions for Assistive Robots Using Machine Learning and Sensor Fusion Technologies', Electronics, vol. 13, no. 16, p. 3285.

5. Selvaggio, M., Cognetti, M., Nikolaidis, S., Ivaldi, S. & Siciliano, B. 2021, 'Autonomy in Physical Human-Robot Interaction: A Brief Survey', IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7989-7996.

6. Xu, P., Zhu, X. & Clifton, D.A. 2023, 'Multimodal Learning With Transformers: A Survey', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 10, pp. 12113-12132

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 24 February 2025
04:00PM

Interview Date
3 April 2025

Preferred student start date
15 September 2025

Applying

Apply Online  

Contact supervisor

Dr Philip Vance

Other supervisors