Bio‑Inspired Multi‑Modal Perception for Dynamic Adaptation in Robotic Formation Flight

About the Project

Supervisory Team: Dr Sergio Araujo-Estrada, Dr Alex Wittig and Dr Jorn Cheney

Flying robots must work together reliably even when vision, GPS, or communications fail. This project explores bio‑inspired robotics, based in our new Aerospace Robotics Control & Simulation (ARCS) facility, where You'll use a KUKA KR10 robot arm to collect data, build intelligent sensing models, and develop control and simulation tools for autonomous aircraft.

Flying robots must work together reliably even when vision, GPS, or communications are unreliable or unavailable. This project explores how bio‑inspired robotics can help autonomous aircraft adapt to changing conditions and continue operating safely and efficiently in complex, real‑world environments.

You'll be based in the new Aerospace Robotics Control and Simulation (ARCS) facility, working with advanced experimental and simulation tools. A key part of the project involves using a KUKA KR10 industrial robot arm to support accurate, repeatable data collection for developing advanced sensing and control methods. The research focuses on enabling robotic aircraft to fly in formation by combining multiple sensing approaches inspired by nature, including vision, sound, and airflow sensing.

Central themes for this work are dynamic adaptation, and resilience and graceful degradation. By dynamic adaptation we mean designing systems that can adjust their sensing strategies and control behaviour in real time as environmental conditions, mission objectives, or available sensors change. While resilience and graceful degradation means ensuring that the system continues to function safely and effectively even when individual sensors, GPS, or communications are lost.

Your work will be structured around three main work packages:

• multi‑modal data collection and modelling: using experimental and synthetic data to develop robust bio‑inspired perception methods
• adaptive perception and control development: focusing on real‑time sensor fusion, dynamic adaptation, and fault tolerance
• simulation and experimental validation: testing formation‑flight behaviours and resilience under realistic operating conditions

This project is well suited to anyone interested in robotics, aerospace, control, or autonomous systems, and we strongly encourage applications from candidates of all backgrounds who are excited by hands‑on, impactful research.

Entry requirements

You must have a UK first-class honours degree, or its international equivalent, in one of the following:

• engineering
• robotics
• aerospace
• control
• computer Science
• mathematics
• a closely related discipline

You should demonstrate strong knowledge in at least one of the following areas:

• robotics
• autonomous systems
• control theory
• perception
• aerospace systems

Desirable skills:

• experience in experimental robotics, sensing, simulation, or data‑driven modelling
• expertise in programming for robotic or embedded systems (e.g. Python, C/C++, ROS), electronics development (e.g., ARM, Arduino), or sensor integration
• prior exposure to research activities, such as a research project, thesis, internship, or publication

Motivation, curiosity, and a willingness to learn across disciplines are considered as important as prior experience.

You must be UK national and able to successfully pass DSTL security vetting.

Fees and funding

For UK students, tuition fees will be paid and you'll receive an enhanced stipend of £25000 per year (about 25% above the EPSRC rate) with a 5% increase to adjust for inflation each subsequent year.

How to apply

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)