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PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision

Meier, Lorenz ; Tanskanen, Petri ; Heng, Lionel ; Lee, Gim ; Fraundorfer, Friedrich ; Pollefeys, Marc

In: Autonomous Robots, 2012, vol. 33, no. 1-2, p. 21-39

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    Title
    • PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision
    Author
    • Meier, Lorenz. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    • Tanskanen, Petri. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    • Heng, Lionel. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    • Lee, Gim. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    • Fraundorfer, Friedrich. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    • Pollefeys, Marc. ETH Zurich, CAB G 86.3, Universitaetstr. 6, 8092, Zurich, Switzerland
    Document Type
    • Postprint
    Language
    • English
    Published in
    • Autonomous Robots, 2012, vol. 33, no. 1-2, p. 21-39. Springer US; http://www.springer-ny.com
    Other Version
    OAI-PMH Identifier
    • oai:doc.rero.ch:317148
    Summary
    We describe a novel quadrotor Micro Air Vehicle (MAV) system that is designed to use computer vision algorithms within the flight control loop. The main contribution is a MAV system that is able to run both the vision-based flight control and stereo-vision-based obstacle detection parallelly on an embedded computer onboard the MAV. The system design features the integration of a powerful onboard computer and the synchronization of IMU-Vision measurements by hardware timestamping which allows tight integration of IMU measurements into the computer vision pipeline. We evaluate the accuracy of marker-based visual pose estimation for flight control and demonstrate marker-based autonomous flight including obstacle detection using stereo vision. We also show the benefits of our IMU-Vision synchronization for egomotion estimation in additional experiments where we use the synchronized measurements for pose estimation using the 2pt+gravity formulation of the PnP problem