About the Project
A fully funded PhD studentship is available for an outstanding graduate with specific interest on robotics, control as well as signal processing techniques. The project is in close collaboration with the industry partner to develop an intelligent system that addresses the inherent uncertainty in the nuclear industry case study environments. The results will be used for condition monitoring of the available assets and waste storage sites. Engineering research at Lancaster University has been rated as world leading in the 2014 Research Excellence Framework (REF) and you will join a dedicated team of scientists working on a range of exciting topics in robotics.
Sensor networks has a great potential to develop innovative technologies in condition monitoring and inspection of the nuclear legacy. Compared to the fixed sensor network endowing mobility by using UAV, AUV, or wheel-based robots shows a superior performance in terms of its adaptability and high-resolution sampling capability. This is especially important in dynamic and hazardous environments which are inaccessible for measurements by human.
Achieving this aim, necessitates the study of distributed learning and control methodologies for autonomous vehicles. The intelligent system in this case consists of a collection of mobile sensing agents that are low-cost, low-power, multifunctional and communicate in short distances. The processing capability of each agent supports higher-level decision making and distributed coordination of mobile sensing agents to achieve a global goal. This involves various tasks of particular interest to the nuclear industries, such as detecting the spread of nuclear radiation, monitor the temperature and humidity distribution in the quiescent buildings, locate the leakage of the contaminant (gas, oil, etc) or hot spots such as drums in the storage sites.
The algorithm consists of two stages. The first step is to estimate the uncertain scalar field of interest (temperature, humidity, gas pressure, etc) by collecting the spatio-temporal data collected by each mobile robot (agent) locally.
The next step is to derive the control law for the mobile sensors by considering two measures. The multi robots should move in a way to maximize their sensory information relative to the current uncertainties in the environment model. Moreover, the multiagent system should move to find the sources in the environment.
Eligibility Criteria:
Potential candidates for this position are expected to have the following qualifications
• Should have or expect to achieve a first-class or upper second-class degree in Engineering at the level of MSc, MEng, etc or a lower second with a good Master’s, (or overseas equivalents) in a relevant subject.
• The fund is available for UK/EU students; however, international students could also apply under circumstances.
• Sufficient background on control and signal processing or closely related discipline.
• Practical experiences on implementation of the control algorithms.
• Computer programming skills such as MATLAB are essential for the post.
• You should have excellent interpersonal skills, work effectively in a team and have experience of the preparation of presentations, reports or journal papers to the highest levels of quality.
The suitable candidate should also have been resident in the UK for at least 4 years immediately prior to taking up the position.
Funding Notes
A full standard studentship consists of tuition fees, together with a maintenance grant and research training support. The funding is for 3.5 years and will pay a stipend that is £2K above the standard UKRC rate.
To declare your interest and get further information about the application procedure, please send a copy of your CV along with the cover letter to Dr Allahyar Montazeri ([Email Address Removed])
The formal application should be made via the Lancaster University Postgraduate Admissions Portal once it is reviewed and considered for the position.
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