Aim:
The aim of this PhD is to develop new human cognition inspired algorithms that can learn how humans complete manufacturing tasks while dealing with variations in the environment as well as how they transfer learnt skills between tasks to solve problems.
Background:
Current Human-Robot collaborations are driven by kinaesthetic teaching which requires humans to guide the robot end effectors to do a task. The above technique often works well in environments that are rigid and well structured. However, in situations where the task is often varying and the environment can change, these strategies fail. Furthermore, one of the paradigms that have been created by the machine learning community is the Reinforcement Learning paradigm. Though state of the art reinforcement learning algorithms have given impressive results, they often have shortcomings when the variation in the environment or task increases. On the other hand, natural cognition in humans provide us with a lot of food for thought in creating flexible, resilient and robust artificial intelligent systems.
Objectives:
1. Develop bio-inspired novel algorithms that are able to deal with variations in the environments.
2. Apply the developed algorithms on collaborative manufacturing robots.
3. Validate the algorithms using various use cases.
Research Environment:
Our academic and research staff are world leaders in the study of robotics, signal processing and intelligent systems. This project is based
in the autonomous Systems and Robotics Research Group which carries out world leading research in autonomous processes and autonomous
robotic systems by investigating key research problems of sensing, control, decision making and system integration.
The collective competence of the group is unparalleled in the UK and covers most essential topics of this area: design of autonomous
industrial robots, condition monitoring for fault tolerant autonomous systems, biologically inspired principles of sensing and control, international standards for autonomous robots, self-assembling robotic systems and swarms, advanced software architectures for decision making, autonomous hybrid systems modelling, formal verification, and distributed and parallel control systems.
This project will be conducted in collaboration the Institute of High Performance Computing, which is part of the Agency for Science, Technology and Research, in Singapore (https://www.a-star.edu.sg/) and would involve spending time both in the UK and Singapore.
Award details:
For each student admitted to the 3-year programme, A*STAR will provide the following financial support, whilst the student is in
Singapore:
Living allowance: A monthly stipend of two thousand, five hundred Singapore Dollars (~£1,300) whilst in Singapore.
A one-off settling-in allowance of one thousand Singapore dollars (~£530).
A one-time airfare allowance of one thousand five hundred Singapore dollars (~£800).
One-time IT allowance of eight hundred Singapore dollars (~£425)
Consumables and Bench Fees incurred by students when based at A*STAR in Singapore.
Cost of medical insurance while the student is based at A*STAR.
Medical insurance, Housing subsidy, Conference allowance.
Whilst in Sheffield, students receive primary fees (£4,500 in 21/22)
and stipend at the UKRI rate (£15,609 in 2021/22). In addition, students may be able to claim up to £500 from Sheffield towards the costs of an airfare back to the UK whilst they are in Singapore in order to make a home visit. This will normally only be available for students who meet the normal expectations of spending approximately half of the programme (1.5 years) in Singapore.
Please note that there is no funding for RTSG, conference expenses, or additional bench fees while in Sheffield. Those deemed necessary should be provided by the supervisor/department as appropriate.
To apply for the studentship, applicants need to apply directly to the University of Sheffield using the online application system. Please name
Dr John Oyekan as your proposed supervisor.
Complete an application for admission to the standard Automatic Control and Systems Engineering PhD
programme: http://www.sheffield.ac.uk/postgraduate/research/apply
Applications should include a research proposal, CV, transcripts and two references.
The research proposal (up to 4 A4 pages, including references) should outline your reasons for applying for this scholarship and how you
would approach the researching, including details of your skills and experience.
Continue with Facebook
