Visual Motion Tracking and Sensor Fusion for Kite Power Systems
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Author / Producer
Date
2018
Publication Type
Book Chapter
ETH Bibliography
yes
Citations
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OPEN ACCESS
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Abstract
An estimation approach is presented for kite power systems with ground-based actuation and generation. Line-based estimation of the kite state, including position and heading, limits the achievable cycle efficiency of such airborne wind energy systems due to significant estimation delay and line sag. We propose a filtering scheme to fuse onboard inertial measurements with ground-based line data for ground-based systems in pumping operation. Estimates are computed using an extended Kalman filtering scheme with a sensor-driven kinematic process model which propagates and corrects for inertial sensor biases. We further propose a visual motion tracking approach to extract estimates of the kite position from ground-based video streams. The approach combines accurate object detection with fast motion tracking to ensure long-term object tracking in real time. We present experimental results of the visual motion tracking and inertial sensor fusion on a ground-based kite power system in pumping operation and compare both methods to an existing estimation scheme based on line measurements.
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Publication status
published
Editor
Book title
Airborne Wind Energy
Journal / series
Volume
Pages / Article No.
413 - 438
Publisher
Springer
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
08814 - Smith, Roy (Tit.-Prof.) (ehemalig) / Smith, Roy (Tit.-Prof.) (former)
Notes
Funding
141836 - Autonomous Airborne Wind Energy (A2WE) (SNF)