Vision based Position Control for MAVs using one single Artificial Landmark

This paper presents a real-time vision based algorithm for 5 degrees-offreedom pose estimation and set-point control for a Micro Aerial Vehicle (MAV). The camera is mounted on-board a quadrotor helicopter. Camera pose estimation is based on the appearance of two concentric circles which are used as landmark. We show that that by using a calibrated camera, conic sections, and the assumption that yaw is controlled independently, it is possible to determine the six degrees-of-freedom pose of the MAV. First we show how to detect the landmark in the image frame. Then we present a geometric approach for camera pose estimation from the elliptic appearance of a circle in perspective projection. Using this information we are able to determine the pose of the vehicle. Finally, given a set point in the image frame we are able to control the quadrotor such that the feature appears in the respective target position. The performance of the proposed method is presented through experimental results. Multimedia Material Please note that this paper is accompanied by a high definition video which can be found at the following address: http://www.youtube.com/watch?v=SMFR2aFR2E0 In this video, the algorithm described in this paper is used for automatic take-off, hovering, and landing. The navigation part is performed using another approach which is described in [1]. In the video, you can also see the landmark described in this paper, composed of two concentric black and white circles. The rectangular box surrounding the landmark denotes the search area used to speed up the tracking of the landmark. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 231855 (sFly). Daniel Eberli is currently Master student at the ETH Zurich. Davide Scaramuzza is currently senior researcher and team leader at the ETH Zurich. Stephan Weiss is currently PhD student at the ETH Zurich. Roland Siegwart is full professor at the ETH Zurich and head of the Autonomous Systems Lab. D. Eberli · D. Scaramuzza · S. Weiss · R. Siegwart ETH Autonomous Systems Laboratory, 8092, Zurich, Switzerland, www.asl.ethz.ch E-mail: [email protected], [email protected], [email protected], [email protected] 2 The detection, conversely, is done using the entire image. The cables visible are used for streaming the images to the laptop and for securing the helicopter during flight.