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Wind field estimation for autonomous dynamic soaring

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4 Author(s)

A method for distributed parameter estimation of a previously unknown wind field is described. The application is dynamic soaring for small unmanned air vehicles, which severely constrains available computing while simultaneously requiring updates that are fast compared with a typical dynamic soaring cycle. A polynomial parameterization of the wind field is used, allowing implementation of a linear Kalman filter for parameter estimation. Results of Monte Carlo simulations show the effectiveness of the approach. In addition, in-flight measurements of wind speeds are compared with data obtained from video tracking of balloon launches to assess the accuracy of wind field estimates obtained using commercial autopilot modules.

Published in:

Robotics and Automation (ICRA), 2012 IEEE International Conference on

Date of Conference:

14-18 May 2012