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Improving swarm coordination with the application of heterogeneous potential field effects (Advert Reference: RDF19/EE/CIS/ELIOT)

  • Full or part time
  • Application Deadline
    Friday, January 25, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Drones are becoming an everyday sight and with the advent of Amazon deliveries they are set to become even more common place. The use of single drones to carry out a task is also becoming more common, with the introduction of crop checking and searching for missing individuals in mountain rescue missions. However, there is now an increasing interest in the use of swarms of drones (agents) to solve various tasks more effectively and with a degree of redundancy to improve ‘mission’ outcomes. Currently, when modelling or deploying physical implementations of swarms, coordination is often achieved using homogeneous potential fields. This approach lends itself to analysis using inter-agent distances and simplifies the algorithms required to create a swarming effect.

The aim of this project is to investigate the application of heterogeneous field effects to improve swarm frontiers. When swarms are used to create mobile networks or to carry out reconnaissance tasks the distribution of agents has a tendency to be uniform. Increasing agent density at the swarm frontier increases sensor density and potentially improves the application of the swarm.
This project would be suitable for a student who has knowledge in the following areas:

• Programming (in any language e.g. C, C++, Python)
• Mathematical modelling
• Machine learning
• Robotics

The principal supervisor for this project is Neil Eliot.

Eligibility and How to Apply:

Please note eligibility requirement:

• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF19/EE/CIS/ELIOT) will not be considered.

Deadline for applications: Friday 25 January 2019
Start Date: 1 October 2019

Northumbria University is an equal opportunities provider and in welcoming applications for studentships from all sectors of the community we strongly encourage applications from women and under-represented groups.

Funding Notes

The studentship is available to Students Worldwide, and covers full fees and a full stipend, paid for three years at RCUK rates (for 2018/19, this is £14,777 pa).

References

Eliot, Neil (2017) Methods for the efficient deployment and coordination of swarm robotic systems. Northumbria University, Newcastle upon Tyne, UK

Eliot N, Kendall D, Brockway M “A New Metric for the Analysis of Swarms using Potential
Fields” in IEEE Access, 2018

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