Robust Autonomous Navigation Based on Artificial Intelligence Approaches PhD

This is an excellent fully-funded PhD opportunity in the area of autonomy, navigation, and artificial intelligence, aiming to pave a way to wider implementation of autonomous systems, such as drones or self-driving cars into our everyday life.

Although these systems are in use for some years, robustness of their autonomous operations, including the ability to navigate safely in complex urban environments, is still an open challenge. This project will focus on the development of assured AI-based navigation solution for unmanned aerial vehicle (UAV), which allows for reliable operation in safety-critical missions when satellite navigation, such as GPS or GNSS is not available or severely degraded in quality. 

Assured navigation is one of the key enabling technologies for new emerging applications of autonomous systems such as drones and cars within the Smart City and Urban Aerial Mobility ecosystems. In addition to economical and societal benefits, autonomous systems in these emerging areas should be able to provide resilience in cases of disasters and pandemics, for example, by enabling autonomous deliveries in conditions of viral threats (such as COVID 19) without essential risks for couriers or delivery recipients.

Current solutions do not provide the required level of accuracy and resilience when satellite navigation is challenging, e.g. in urban canyons. There is a growing and urgent need worldwide in high precision hybrid navigation technologies, able to provide the assured performance of unmanned vehicles in autonomous safety-critical operations. Therefore, this project aims to develop a cost-effective assured navigation solution for autonomous systems, suitable for safety-critical missions in environments where satellite-based navigation is either performance-degraded or denied.  Cranfield is an exclusively postgraduate university in technology and management, widely recognised for delivering outstanding transformational research that meets the needs of business, government, and the wider society.

EPSRC through their funding program offers this collaboration research opportunity between Cranfield and Spirent Communications, who is the leading global provider of automated test and assurance solutions for networks, cybersecurity, and positioning. This project will offer high accuracy robust hybrid navigation and positioning solution that utilizes multiple localization and navigation information sources in an efficient framework based on deep learning techniques.  The project also offers extensive training at both Spirent Communications and Cranfield, covering essential skills in artificial intelligence, sensor fusion, positioning, corresponding simulation software, and hardware.

At Cranfield, you will have access to the University’s core skills training programmes for PhD students, while Spirent facilitates the development of industry-specific transferrable skills through involvement in teamwork, preparation, and participation in workshops, and showcasing to customers. As a part of this project, you will also benefit from multiple opportunities to present your work at major international conferences and industrial events. In this exciting project, you will be exposed to the latest technological developments and learn from both academic and industrial experts in this area.

Being supported by extensive training options for both technical and transferrable skills will help you to become well prepared for your future success in either industry or academia.

At a glance

  • Application deadline14 Dec 2020
  • Award type(s)PhD
  • Start date01 Feb 2021
  • Duration of award3 years
  • EligibilityUK, EU
  • Reference numberSATM176


1st Supervisor: Dr. Ivan Petrunin

2nd Supervisor: Prof. Weisi Guo

Entry requirements

Applicants should have a first or second class UK honors degree or equivalent in a related discipline.

This project would suit someone with:

  • A strong background in computer programming (e.g. C/C++, Python, Rust).
  • A hands-on approach with skills in the implementation of control/fusion/learning-based techniques in the areas of robotics, unmanned, or autonomous systems.
  • Demonstrable knowledge in statistical modelling and data analytics.
  • Keen to work with equipment and electronics.
  • Be comfortable with working in R&D team of engineers.


To be eligible for this funding, applicants should have no restrictions regarding how long they can stay in the UK, i.e.: 

  • Have no visa restrictions or 
  • The applicant has “settled status” and has been “ordinarily resident” in the UK for 3 years prior to the start of studies and has not been residing in the UK wholly or mainly for the purpose of full-time education (this does not apply to UK or EU nationals).

Due to funding restrictions, all EU nationals are eligible to receive a fees-only award if they do not have “settled status” in the UK.

About the sponsor

Sponsored by EPSRC, Cranfield University, and Spirent Communication, this studentship will provide a selected eligible candidate bursary up to £20,000 (tax-free) plus fees for three years. You will have an opportunity to travel to international conferences and meet industrial collaborators for training, guidance, and experimentation.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

For further information please contact:

For further information please contact:      
Name: Dr. Ivan Petrunin
Email: [email protected]
T: (0) 1234 750111 Ext: 8262

If you are eligible to apply for this studentship, please complete the online application form.