2025-08-06 ミネソタ大学
Using autonomous drones, researchers are able to create a 3D reconstruction of the smoke plume and improve analysis of flow patterns. Photo Credit: Jiarong Hong Lab
＜関連情報＞
- https://cse.umn.edu/college/news/ai-equipped-aerial-robots-help-track-and-model-wildfire-smoke
- https://www.sciencedirect.com/science/article/abs/pii/S0048969725011039
多視点ドローン群を用いた煙の拡散の3次元特性化 3D characterization of smoke plume dispersion using multi-view drone swarm
Nikil Krishnakumar, Shashank Sharma, Srijan Kumar Pal, Jiarong Hong
Science of The Total Environment Available online: 29 April 2025
DOI:https://doi.org/10.1016/j.scitotenv.2025.179466
Highlights
- Autonomous drone swarm for 3D high resolution measurements of smoke plume dispersion
- Dynamic multiview imaging via coordinated swarm of one manager and four worker drones
- Integration of deep learning tools for 3D plume reconstruction in complex environment
- Field validation reveals plume volume, direction, shape with second-level detail
- Versatile platform for fire modeling, air-quality monitoring, and disaster response
Abstract
This study presents an advanced multi-view drone swarm imaging system for the three-dimensional characterization of smoke plume dispersion dynamics. The system comprises a manager drone and four worker drones, each equipped with high-resolution cameras and precise GPS modules. The manager drone uses image feedback to autonomously detect and position itself above the plume, then commands the worker drones to orbit the area in a synchronized circular flight pattern, capturing multi-angle images. The camera poses of these images are first estimated, then the images are grouped in batches and processed using Neural Radiance Fields (NeRF) to generate high-resolution 3D reconstructions of plume dynamics over time. Field tests demonstrated the system’s ability to capture critical plume characteristics including volume dynamics, wind-driven directional shifts, and lofting behavior at a temporal resolution of about 1 s. The 3D reconstructions generated by this system provide unique field data for enhancing the predictive models of smoke plume dispersion and fire spread. Broadly, the drone swarm system offer a versatile platform for high resolution measurements of pollutant emissions and transport in wildfires, volcanic eruptions, prescribed burns, and industrial processes, ultimately supporting more effective fire control decisions and mitigating wildfire risks.
