Developing a sentient digital twin for safe and resilient robotic systems

The next-generation robotic systems require the ability to learn, adapt, and operate safely in complex environments to ensure safe and resilient operation. Through the development of sentient digital twins – a virtual counterpart of the physical robot – this project explores cutting-edge simulations and AI techniques to allow truly self-adaptive control algorithms.  

This study focuses on robotic autonomous ground vehicles that may be deployed within hazardous environments, for example, to support first responders during natural disasters. The development of a digital twin that will be capable to automatically react and update its virtual representation according to the environment will be the core of the research work. This ‘sentient’ digital twin will enable precise, quick adjustments to the vehicle's controllers to allow operation in unknown terrain and/or even in the event of damage. 

The project will start with the study of the integration of generative AI techniques with a virtual vehicle model capable of generating realistic sensory data. This first step equips the digital twin to dynamically adapt to the current operating conditions. Through training via scenario simulations, the digital twin will learn to employ self-adapting control strategies, allowing it to discern optimal courses of action in challenging situations and ensure secure vehicle operations. The developed digital twin and adaptive control strategies will be tested in simulation and through experimental data obtained from the in-house autonomous vehicle ZEBRA (Zero Emission test Bed for Research on Autonomous driving).

Open to both UK and international candidates.

Up to 30% of our UKRI-funded studentships can be awarded to candidates paying international rate fees. Find out more about eligibility.

You will need to meet the minimum entry requirements for our PhD programme.

​​The successful candidate is expected to be highly motivated and must hold a minimum of a 2:1 Bachelor’s level degree (or international equivalent) in Mechanical Engineering, Robotics, Control Systems, AI, or a related field. Proficiency in programming languages like Python, C++, and MATLAB is essential. Practical experience in generative AI, control systems, and robotics is desirable. The candidate should possess strong analytical and problem-solving abilities, coupled with excellent written and verbal communication skills. Independence in research endeavours and quick adaptation to new technologies are highly valued.​