Swarming Algorithms used to achieve Goal based Missions PhD

Background

This is an exciting opportunity for a fully-funded PhD studentship in the Centre for Autonomous and Cyber-Physical Systems at Cranfield University, in the field of autonomy and multiple UAS. This PhD investigates decentralised control and level of unit-level autonomous intelligence for multiple UAS operation. This research is sponsored by BAE Systems under Industrial Cooperative Awards in Science & Technology (ICASE) 2020.

Using swarms to conduct missions is not a new topic and many companies are looking at the application of large numbers of drones to achieve these missions. However, these ‘swarms’ are typically controlled using a centralised system such as a ground station or manned aircraft/ vehicle, and this is not considered as exploiting true swarm capabilities due to the command structure. The advantage of emergent swarm behaviours is to overcome the excessive operator Command and Control manpower utilisation and to become resilient, and not reliant upon hierarchical, single point of failure control nodes. (e.g. Swarms dispersed for concentrated attack, extended communications relays and wider area surveillance.)

The proposed research is to identify the characteristics which determine the level of intelligence and inter-unit communications, necessary to establish and affect different emergent behaviours from the overall swarm. The research will identify how different emergent behaviours could be derived from a parametrised simple deployed algorithm.

Cranfield is an exclusively postgraduate university that is a global leader for education and transformational research in technology and management. This PhD will be hosted by the Centre for Autonomous and Cyber-Physical Systems. The Centre for Autonomous and Cyber-Physical Systems is one of the world’s largest centres of postgraduate education and research, with over 200 MSc and PhD students.

In terms of facility, Cranfield University has a range of specialist research facilities available for different research activities (e.g. Digital Aviation Research and Technology Centre). The facility operates as a collaborative and flexible space with specialist equipment available for indoor/outdoor flight tests for UAS systems. Also, the Centre for Autonomous and Cyber-Physical Systems offers the environment for algorithm development and simulation. Also, the centre can offer support, assistance with analysis, and method development for research.

You will be suggesting recommendations on what algorithms are most suited to Goal-based missions; this may also include a way of auditing the mission and validating the swarm behaviours to the users/customers to gain credibility. You will be asked to consider the Maritime environment as an area of particular interest. This research is expected to include modelling and potential physical implementation in association with BAE Systems.

You will be encouraged and supported in publishing own work in high-quality peer-reviewed journals. Also, you will have opportunities and supports to present your work at the relevant UK and international conferences.

You will obtain knowledge on the technologies for the related disciplines, experience the procedures of algorithm development, and learn skills for simulations and flight tests.

Sponsorship

Sponsored by EPSRC and BAE Systems, this studentship will provide a bursary of up to £18,000 (tax free) plus fees* for four years.

Entry requirements

Applicants must have a first- or second-class degree, and a Master’s degree, both in engineering or a related area. A background in robotics, automatic control, and/or AI/ML would be a distinct advantage, as would experience in UAS and flight test.

How to apply

If you are eligible to apply for this studentship, please complete the online application form by clicking on ’Visit Website’.

For further information please contact:

Professor Antonios Tsourdos
Email: [Email Address Removed]
T: (0) 1234 750111 Ext: 4672

or Professor Gokhan Inalhan
Email: [Email Address Removed]
T: (0) 1234 758274