Understanding and predicting human movement is an important scientific endeavour with applications to rehabilitation, security/surveillance, smart environments, robotics, etc. Specifically, in Smart Environments (SE) and Human-Robot Interaction (HRI) models of human movement allow to anticipate human actions, therefore enabling predictive automation – e.g. in smart homes –, to detect irregular motion patters, and to adapt robot behaviour in view of a human’s intentions.
This project will develop a novel methodology for modelling human-like movement using advanced machine-learning techniques. Specifically, the work will focus on modelling human navigation in indoor environments, and object manipulation. The new methodology will make use of dynamical systems learning and non-linear systems identification as a comparative baseline. The models obtained will be tested in a smart environment setting to predict people’s behaviour and to detect deviation from normal movement.
The goal of this project is to develop, implement and test a novel methodology for the modelling and generation of human-like movement. The expected research outcome is a novel methodology to obtain movement models applied to human motion prediction and comparison in Smart Environments with applications to other areas like human-like motion generation in Robots.
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.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University offers the following levels of support:
The following scholarship options are available to applicants worldwide:
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.
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.
Due consideration should be given to financing your studies. Further information on cost of living
Submission deadline
Monday 19 February 2018
12:00AM
Interview Date
9 to 23 March 2018
Preferred student start date
Mid September 2018
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