Postgraduate research project

Bio‑inspired multi‑modal perception for dynamic adaptation in robotic formation flight

Funding
Fully funded (UK only)
Type of degree
Doctor of Philosophy
Entry requirements
First-class honours degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

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.

The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.