About the project
The next generation of unmanned aerial vehicles (UAVs) must be capable of independent perception, reasoning, and adaptation in complex and dynamic environments. This PhD project aims to design a UAV platform equipped with intelligent sensing, physics-based modelling, and intelligent real-time decision-making to achieve situational awareness far beyond what is possible today.
The focus of this research will be the design and validation of a miniaturised, low-power sensing system capable of identifying environmental features such as turbulence and thermals. These conditions can be exploited to improve flight efficiency and extend endurance, enabling UAVs to operate intelligently and sustainably.
Through a combination of novel sensor architectures, embedded AI algorithms, and flight testing, the successful candidate will help to advance the frontier of self-sustaining aerial systems.
The research will investigate the integration of an intelligent sensor suite combining acoustic, pressure, and temperature measurements for real-time environmental mapping. Using onboard machine learning models, the UAV will be capable of autonomous decision-making and energy-aware navigation in noisy and uncertain conditions.
This project offers the opportunity to contribute to the development of autonomous, energy-aware UAVs for environmental monitoring, climate research, and the future of sustainable aviation.
Experimental testing and lab training will be provided.
