Toward model free atmospheric sensing by aerial robot networks in strong wind fields

Authors:
Jack Elston;Maciej Stachura;Eric W. Frew;Ute C. Herzfeld
Affiliations:
Aerospace Engineering Sciences, University of Colorado, Boulder, CO;Aerospace Engineering Sciences, University of Colorado, Boulder, CO;Aerospace Engineering Sciences, University of Colorado, Boulder, CO;Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

Citing 4
Cited 0

Ordered Upwind Methods for Static Hamilton--Jacobi Equations: Theory and Algorithms

SIAM Journal on Numerical Analysis
Call and response: experiments in sampling the environment

SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Path Planning for Autonomous Underwater Vehicles

IEEE Transactions on Robotics
Decentralized Environmental Modeling by Mobile Sensor Networks

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a system for in situ atmospheric sensing using an aerial robot system in the presence of a strong wind field. The geostatistical concept of the variogram is used to characterize regions of the environment with high variability, which is assumed to correlate with scientific interest. After regions of interest are identified, ordered upwind methods are used to generate feasible trajectories in the face of strong background wind. The feasible trajectories are combined with the variogram characterization to select feasible paths that travel through the regions of highest interest. The system is tested in simulation using data from a simulated severe storm.