This PhD will develop cooperative guidance and navigation methods to allow small formations of Uninhabited Air Vehicles (UAVs) to investigate and explore otherwise ill-defined regions while employing passive RF sensors (i.e. providing only angle of arrival and signal-strength measurements) – providing both contextual information (what?) and localisation information (where?).
Current UAVs tend to be directly controlled by an operator or to fly prescribed, pre-planned routes. With recent improvements in processing speed and artificial intelligence, it is likely that future UAVs will have more flexibility and provide a degree of coordination and cooperation within an overall defined mission. Such automated control of UAVs will be significantly enhanced by the ability to share identification and position information across platforms, particularly for the case of Passive RF sensors where individual measurements are ambiguous. It will allow a top-level requirement to be fixed by an operator whilst permitting the UAVs a degree of flexibility to allocate resources appropriately to meet this requirement.
The key challenges in this work are in the efficient prioritisation of the individual tasks required to meet the overarching mission requirement, the high degree of uncertainty associated with the abilities of the sensors, and the optimisation of the scheduling of these tasks, which may include different sensor capabilities The choice of scenarios considered, the properties of the UAVs, and the task requirements will be developed in collaboration with the industrial partner, MBDA.
This project is part of the EPSRC Funded CDT in Distributed Algorithms: The What, How and where of Next-Generation Data Science. https://www.liverpool.ac.uk/research/research-at-liverpool/research-themes/digital/cdt-distributed-algorithms/
The University of Liverpool is working in partnership with the STFC Hartree Centre and other industrial partners from the manufacturing, defence and security sectors to provide a 4 year innovative PhD training course that will equip over 60 students with the essential skills needed to become future leaders in data science, be it in academia or industry.
Every project within the centre is offered in collaboration with an Industrial partner who as well as providing co-supervision will also offer the unique opportunity for students to access state of the art computing platforms, work on real world problems, benchmarking and data. Our graduates will gain unparalleled experiences working across academic disciplines in highly sought-after topic areas, answering industry need.
As well as learning from academic and industrial world leaders, the centre has a dedicated programme of interdisciplinary research training including the opportunity to undertake modules at the global pinnacle of Data science teaching. A large number of events and training sessions are undertaken as a cohort of PhD students, allowing you to build personal and professional relationships that we hope will lead to research collaboration either now or in your future.
The learning nurtured at this centre will be based upon anticipation of the hardware recourses arriving on desks of students after they graduate, rather than the hardware available today.