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UAV Bridging and Real-time Deployment Protocols for Disaster & Emergency Response Scenarios (PARRG_U18SCID)

University of East Anglia - Computing Sciences

Qualification Type: PhD
Location: Norwich
Funding for: UK Students, EU Students
Funding amount: £14,777 annual stipend
Hours: Full Time
Placed On: 9th November 2018
Closes: 18th January 2019
Reference: PARRG_U18SCID

Start date:  1 April 2019

No. of positions available: 1


Primary: Professor Gerard Parr
Secondary: Dr Edwin Ren
Industrial Mentor: Dr Carla Di Cairano-Gilfedder  

Project description: 

Unmanned Aerial vehicles (UAVs) play an invaluable role in information collection and data fusion in a variety of applications such as disaster response, search and rescue, surveillance, forest fire monitoring and provision of temporary communications when terrestrial/mobile networks are disrupted.  This project will tackle the problem of maintaining connectivity and collision avoidance for UAVs involved in critical network infrastructure management for emergency and special event base-station provision or disaster management.  Rotor-based Unmanned Aerial Vehicles are gaining increased research interest due to their versatility and increased functionality in applications such as infrastructure monitoring and re-design (such as fibre cable laying across rivers).  However, because of their mobility and the complexity of deployed environments, the UAV platforms require real-time solutions for constant position awareness and collision avoidance with other UAVs and the surrounding physical environment.  Also, to maximise information gained from the deployment environment, such platforms require increased autonomy to coordinate the actions of multiple UAVs and interaction with ground-based systems.  Such challenges require the development of numerous flight planning and coordination algorithms designed to maximise information gain during sensing missions. In some extreme cases, GPS signals may be lost.  By incorporating bridging and collision protocols into the search strategies, UAVs can adapt to the radio propagation characteristics of their environment, and integrate flight path and network routing decisions, so that uncertainty and the effect of UAV position on network performance are taken into account to ensure the success of a mission.  This PhD project will tackle the problem of maintaining connectivity and collision avoidance on UAVs involved in a number of application scenarios provided by BT as part of a funded Internship that will be arranged at an appropriate time during the PhD project and managed by our BT assigned industrial mentor Dr Carla Di Cairano-Gilfedder (subject to approvals and progress).

Person Specification:

 Acceptable first degree: Computer Science, Physics, Mathematics, Engineering or other numerate discipline. Standard minimum entry requirement is 2:1, but it is desirable that applicants will have a 1st Class Honours Degree in a related subject and hopefully a Masters with experience of communications networking protocols, mathematical modelling and simulation.

Funding notes:

This 3 year PhD studentship is funded by the Faculty of Science.  Funding is available to UK/EU applicants only and comprises home/EU tuition fees and an annual stipend of £14,777.

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