TY - GEN
T1 - The flying anemometer
T2 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
AU - Tomić, Teodor
AU - Schmid, Korbinian
AU - Lutz, Philipp
AU - Mathers, Andrew
AU - Haddadin, Sami
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - We consider the problem of estimating the wind velocity perceived by a flying multicopter, from data acquired by onboard sensors and knowledge of its aerodynamics model only. We employ two complementary methods. The first is based on the estimation of the external wrench (force and torque) due to aerodynamics acting on the robot in flight. Wind velocity is obtained by inverting an identified model of the aerodynamic forces. The second method is based on the estimation of the propeller aerodynamic power, and provides an estimate independent of other sensors.We show how to calculate components of the wind velocity using multiple aerodynamic power measurements, when the poses between them are known. The method uses the motor current and angular velocity as measured by the electronic speed controllers, essentially using the propellers as wind sensors. Verification of the methods and model identification were done using measurements acquired during autonomous flights in a 3D wind tunnel.
AB - We consider the problem of estimating the wind velocity perceived by a flying multicopter, from data acquired by onboard sensors and knowledge of its aerodynamics model only. We employ two complementary methods. The first is based on the estimation of the external wrench (force and torque) due to aerodynamics acting on the robot in flight. Wind velocity is obtained by inverting an identified model of the aerodynamic forces. The second method is based on the estimation of the propeller aerodynamic power, and provides an estimate independent of other sensors.We show how to calculate components of the wind velocity using multiple aerodynamic power measurements, when the poses between them are known. The method uses the motor current and angular velocity as measured by the electronic speed controllers, essentially using the propellers as wind sensors. Verification of the methods and model identification were done using measurements acquired during autonomous flights in a 3D wind tunnel.
UR - http://www.scopus.com/inward/record.url?scp=85006410128&partnerID=8YFLogxK
U2 - 10.1109/IROS.2016.7759264
DO - 10.1109/IROS.2016.7759264
M3 - Conference contribution
AN - SCOPUS:85006410128
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 1637
EP - 1644
BT - IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 October 2016 through 14 October 2016
ER -