Monitoring the evolution of clouds with UAVs


We study the problem of monitoring the evolution of atmospheric variables within low-altitude cumulus clouds with a fleet of Unmanned Aerial Vehicles (UAVs). To tackle this challenge, two main problems can be identified: i) creating on-line maps of the relevant variables, based on sparse local measurements; ii) designing a planning algorithm which exploits the obtained map to generate trajectories that optimize the adaptive data sampling process, minimizing the uncertainty in the map, while steering the vehicles within the air flows to generate energetic-efficient flights. Our approach is based on Gaussian Processes (GP) for the mapping, combined with a stochastic optimization scheme for the trajectories generation. The system is tested in simulations carried out using a realistic three-dimensional current field. Results for a single UAV as well as for a fleet of multiple UAVs, sharing information to cooperatively achieve the mission, are provided.

DOI: 10.1109/ICRA.2016.7487145

7 Figures and Tables

Cite this paper

@article{Renzaglia2016MonitoringTE, title={Monitoring the evolution of clouds with UAVs}, author={Alessandro Renzaglia and Christophe Reymann and Simon Lacroix}, journal={2016 IEEE International Conference on Robotics and Automation (ICRA)}, year={2016}, pages={278-283} }