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

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 e...

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Published in:	Autonomous robots Vol. 33; no. 1-2; pp. 21 - 39
Main Authors:	Meier, Lorenz, Tanskanen, Petri, Heng, Lionel, Lee, Gim Hee, Fraundorfer, Friedrich, Pollefeys, Marc
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.08.2012 Springer Nature B.V
Subjects:	Airborne/spaceborne computers Algorithms Artificial Intelligence Autonomous Computer Imaging Computer vision Control Embedded systems Engineering Flight control Mechatronics Micro air vehicles (MAV) Obstacle avoidance Obstacles Onboard Pattern Recognition and Graphics Robotics Robotics and Automation Robots Synchronism Synchronization Systems design Vision Visual flight Computer vision Stereo vision Micro aerial vehicles Quadrotor
ISSN:	0929-5593, 1573-7527
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Abstract	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.
AbstractList	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. Issue Title: Micro-UAV Perception and Control 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.[PUBLICATION ABSTRACT]
Author	Meier, Lorenz Pollefeys, Marc Heng, Lionel Fraundorfer, Friedrich Lee, Gim Hee Tanskanen, Petri
Author_xml	– sequence: 1 givenname: Lorenz surname: Meier fullname: Meier, Lorenz email: lm@inf.ethz.ch organization: ETH Zurich – sequence: 2 givenname: Petri surname: Tanskanen fullname: Tanskanen, Petri organization: ETH Zurich – sequence: 3 givenname: Lionel surname: Heng fullname: Heng, Lionel organization: ETH Zurich – sequence: 4 givenname: Gim Hee surname: Lee fullname: Lee, Gim Hee organization: ETH Zurich – sequence: 5 givenname: Friedrich surname: Fraundorfer fullname: Fraundorfer, Friedrich organization: ETH Zurich – sequence: 6 givenname: Marc surname: Pollefeys fullname: Pollefeys, Marc organization: ETH Zurich
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Copyright	Springer Science+Business Media, LLC 2012 Autonomous Robots is a copyright of Springer, (2012). All Rights Reserved.
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Snippet	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... Issue Title: Micro-UAV Perception and Control We describe a novel quadrotor Micro Air Vehicle (MAV) system that is designed to use computer vision algorithms...
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SubjectTerms	Airborne/spaceborne computers Algorithms Artificial Intelligence Autonomous Computer Imaging Computer vision Control Embedded systems Engineering Flight control Mechatronics Micro air vehicles (MAV) Obstacle avoidance Obstacles Onboard Pattern Recognition and Graphics Robotics Robotics and Automation Robots Synchronism Synchronization Systems design Vision Visual flight
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Title	PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision
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