Flying Model-Based Gas Tomography (FlyMoGaTo)

• Applicants: Professor Dr. Achim Lilienthal; Dr. Thomas Wiedemann
• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 541018916

In CBRN incidents, accurate spatio-temporal observation of airborne materials is crucial for effective disaster response. This drives the need for autonomous UAVs equipped with gas sensing capabilities that enable data collection in hazardous environments and facilitate reconstruction of spatio-temporal gas distributions the dynamic gas behavior and challenges of comprehensive data interpretation. To address this need, FlyMoGaTo focuses on developing a methodology for autonomous UAV-based gas sensing using open-path laser absorption spectroscopy. Its main objectives are to quantify the spatial and temporal evolution of dispersed airborne material and to locate unknown material sources. The proposal is structured around three key goals, including the development of tomographic reconstruction algorithms that make use of domain knowledge expressed through partial differential equations, the investigation of optimal sampling strategies for UAVs, and the design and validation of a prototype system for open-path measurements. In FlyMoGaTo we intend to create a probabilistic framework for gas dispersion modeling, integrate absorption measurements effectively, and select suitable probabilistic inference algorithms for tomographic reconstruction. The quality of the reconstruction is heavily reliant on the methodology used for data collection. Consequently, our objective is to reduce uncertainties through intelligent sampling strategies and the selection of optimal measurement locations and sensor constellations. The proposal also pertains to the practical deployment of the proposed methodologies on UAV platforms, including designing a prototype system. The validation process will involve demonstrating the functionality and effectiveness of the system in realistic scenarios.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2433: Metrology on flying platforms
• Co-Investigator: Dr. Dmitriy Shutin