About the project
This PhD project focuses on developing advanced algorithms for collective perception and prediction in a distributed UAV swarm to enable real-time wildfire monitoring and forecasting.
Wildfires destroy over 12 million hectares of forest annually, nearly half the size of the UK, causing severe ecological and economic damage. Current monitoring methods lack the spatial and temporal resolution required for early detection and rapid situational awareness.
You will explore how a swarm of Unmanned Aerial Vehicles (UAVs) can autonomously sense, communicate, and reason about wildfire dynamics to produce actionable information. The project will specifically focus on fusion of distributed observations and interaction with a UAV swarm. The goal is to enable a swarm to jointly detect, localise and map fire fronts under uncertainty and partial observability.
Key algorithmic approaches include:
- probabilistic state estimation: implement distributed filtering methods for fusing noisy observations from multiple UAVs
- collective perception algorithms: design decentralized swarm algorithms that allow the robots to share local detections and collectively estimate fire boundaries in real time
- multi-robot coordination: apply consensus algorithms and belief propagation to ensure the swarm maintains a coherent, up-to-date situational map despite intermittent communication
- adaptive sensing strategies using reinforcement learning or adaptive controls to allocate the robot's attention to areas of high uncertain or predicted fire growth.
While the focus of this research will be on developing algorithms using existing data in simulation, the student will have access to multiple small and large aerial platforms to conduct experiments, if interested.
There will be the opportunity to participate in networking events and collaborate with a large consortium of world leading researchers across the UK and US, and if interested, gain hands-on experience with UAVs being developed for wildfire detection and suppression.
This project is part of the UKRI AI Centre for Doctoral Training in AI for Sustainability (SustAI), a 4-year integrated programme (iPhD). You will be part of a dynamic and diverse cohort, benefiting from expert mentorship and interdisciplinary collaboration. The programme includes comprehensive training in sustainability, AI and machine learning, and digital design, preparing students for a career at the forefront of research in this area. Students will have access to state-of-the-art facilities and resources, fostering an environment of innovation and excellence.
The School of Electronics & Computer Science 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.
