About the Project
Eligibility: UK/EU/International
Duration: 3 years 6 months Fixed Term
Application deadline: This opportunity will only remain open until a suitable candidate is identified- early application is therefore advised. Standard University research application closing dates apply: http://www.coventry.ac.uk/research/research-students/making-an-application/
Informal enquiries are essential before application; contact Dr. Zahid Usman or Dr. James Brusey to discuss this opportunity.
Congratulations on taking your first steps toward a Research Degree with Coventry’s Faculty of Engineering and Computing. As an ambitious and innovative University, we’re investing an initial £100m into our new research strategy, ‘Excellence with Impact’ (http://www.coventry.ac.uk/research/about-research-at-coventry/). Through original approaches from world-leading experts, we’re aiming for our research to make a tangible difference to the way we live. As a research student you are an integral part of Coventry’s lively and diverse research community and contribute to our reputation for excellence. With our exceptional facilities and superb support mechanisms (http://www.coventry.ac.uk/research/research-students/research-studentships/research-studentships-the-benefits/) you are afforded every opportunity for academic success.
THE PROJECT
Industrial robots have evolved from slow, low precision, and limited movement machines in the 1950/60s to fast, flexible and versatile machines in the 1990s and 2000s. However, safety fences that consume space and limit human interaction surround most robots. In response, a new type of robot has emerged: the collaborative robot (or cobot), which can work collaboratively and in close proximity with humans. Examples include Yumi (from ABB), KUKA Lightweight Arm, Universal Robot, and Baxter. These new robots are exciting because they:
- enable rapid prototyping of automation,
- make it possible to automate tasks that require human input or collaboration, and,
- change our way of thinking about automation.
Although collaborative robots have great potential, there remain open questions, such as:
- How should a robot share an assembly task with a human?
- How can it learn from demonstration?
- Can collaboration with the human user be learnt?
- What are the societal or psychological impacts on the human user?
A key feature of this project is that it directly engages with industry and the end-user. Unipart Powertrain Application (UPA) will provide the case study problem and the contextual background for the research, thus assisting with validation of any research outcomes. A representative system, including the target robot, will be setup at the Institute of Advanced Manufacturing and Engineering (AME) with support from UPA. UPA will also provide access to their work place, an existing production line, to enable understanding of how a collaborative robotic process compares, both in terms of performance and social or psychological impact. The developed system will be tested in controlled industrial environment at UPA.
It is expected that the project will begin with a brief survey of relevant literature, a series of data gathering experiments with the robot to understand the problem, development of software tools (e.g., simulation, integration of machine learning software), and continue through production of a demonstrator to better understand the problem and domain, and identification of the key research questions. These research questions will lead to a series of experiments. It is expected that writing the thesis should begin early and should continue throughout the project.
ABOUT THE CENTRE/DEPARTMENTS
The Institute for Advanced Manufacturing and Engineering (AME) (http://www.coventry.ac.uk/ame/) is a £32m+ collaboration between Coventry University and Unipart Manufacturing. This project is supported by the Higher Education Funding Council for England’s Catalyst Fund.
AME is has introduced and realised a bespoke ‘Faculty on the Factory Floor’ at Unipart Powertrain Applications company site in the heart of Coventry. This forms the focal point of activity and has state-of-the-art robotic automation, forming, joining, analysis and simulation, metrology and product verification technology.
SUCCESSFUL APPLICANTS
Successful applicants will have:
- A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average, or
- A Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at merit level (60%).
- The potential to engage in innovative research and to complete the PhD within a prescribed period of study
- Language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component).
- Additionally, the successful candidate will have strong computer software development skills (which will be skills tested on application) as well as experience in one or more of the following areas:
- Machine Learning
- Robotics and control
- Learning from Demonstration (LfD)
- Machine Vision and Systems Integration
- Human Psychology and Human Factors Engineering
- Understanding of the manufacturing environment and processes
ELIGIBILITY & APPLICATION PROCEDURE
Application Procedure:
Application information can be found in our how to apply section. Before completing the application please contact Dr. Zahid Usman (http://www.coventry.ac.uk/research/research-directories/researchers/dr-zahid-usman/) or Dr. James Brusey (http://www.coventry.ac.uk/research/research-directories/researchers/james-brusey/) (cc'ing [Email Address Removed] when you do) for an initial informal discussion about the opportunity.
Eligibility:
All UK/EU/International students are eligible to apply that meet the academic requirements, the eligibility criteria can be found making an application page: http://www.coventry.ac.uk/research/research-students/making-an-application/
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