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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Vydáno v:Autonomous robots Ročník 33; číslo 1-2; s. 21 - 39
Hlavní autoři: Meier, Lorenz, Tanskanen, Petri, Heng, Lionel, Lee, Gim Hee, Fraundorfer, Friedrich, Pollefeys, Marc
Médium: Journal Article
Jazyk:angličtina
Vydáno: Boston Springer US 01.08.2012
Springer Nature B.V
Témata:
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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Popis
Shrnutí: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.
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ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-012-9281-4