Research

Bristol Flight Lab’s research spans from fundamental to applied and industrial contexts. See below for a selection of current and past projects.

Intelligent Aerial Robots for Environment and Infrastructure

We are interested in the design, perception, and control of aerial robots to foster sustainable operations. Our work is focussed on aerial-physical interactions in problems such as environmental sensing and aerial repair, and we take a nature-inspired approach to adaptive designs, algorithms, and strategies that are tailored for diverse aerial robots and tasks. We intend to address the intricate challenges posed by dynamic aerial system operations and their environments through continual learning in control design.

Sampling with Drones in Disaster Zones

We are interested in developing novel drone technology to aid applied research in a number of scientific fields. We have worked with volcanologists at the Univeristy of Bristol to develop aircraft that can extract ash samples from eruption plumes at Vocán de Fuego, Guatemala Guatemala and Manam volcano in Papua New Guinea. The international team showed how to take measurements from the air, to supplement those from earth and space, and use them to help determine how likely an eruption is to take place.

Wildlife Monitoring with Drones

We are collaborators on the EU-funded WildDrone Project, an international training network. The project will enable doctoral students to gain skills needed to enable the use of drones as a conservation tool for endangered African wildlife. By working across Europe and Africa, including in the Wadden Sea National Park in Denmark, we aim to enhance wildlife conservation efforts by using autonomous drone technology to monitor wildlife populations.

Vertiport Routing for Drone Takeoff and Landings

This project focuses on developing an innovative system for managing drone traffic at vertiports – specialised airports for vertical takeoff and landing aircraft. The goal is to enable multiple drones to simultaneously takeoff and land, to allow for future urban air mobility hubs. It focuses on creating efficient and safe methods for multiple aircraft to simultaneously operate in confined airspaces. The system was modelled in simulation and in real life using multiple drones. This approach aims to maximize operational capacity while maintaining strict safety standards.

Multispectral sensing for plant ID

Biodiversity loss is a global challenge. Advancements in machine learning have enabled broader data capture and processing to support ongoing conservation efforts. UAVs enable increasingly affordable and high-quality data acquisition. This work uses low-cost multispectral drones to detect and identify of individual plant species via AI object-detection models. Current work is taking place on Lundy Island and large-scale rewinding sites.

Drones for Search and Rescue

UAVs can augment human-led ground and aerial Search and Rescue teams, appropriate vehicles, path planning, and route generation can maximise information gain to increase survival probability. Ergodic, coverage, and other approaches to path planning have advantages under various constraints, and modelling drone and sensor viewpoints in complex terrain and conditions can help develop and evaluate approaches. In collaboration with South Denmark University’s Drone Centre, we have released the SAREnv dataset and benchmarking tool: a simulation environment and a set of scenarios that can be used as a standardised and extensible way of comparing SAR path planning algorithms.