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AR.Drone: Postition Estimation with Kalman Filter

Author(s):

Severin Amrein, Mathias Baer
Conference/Journal:

Semester Group Project, HS12 (10210)
Abstract:

The AR.Drone (AR.Drone 2.0) is a quadrocopter made by Parrot which gets connected to a personal computer by WLAN. This device controls the AR.Drone by sending configuration and movement commands and receives data like video streams, temperature, battery state and more. To be able to control the AR.Drone we have to know its exact position. This can be achieved by committing the video stream to a Parallel Tracking And Mapping (PTAM) program in order get the coordinates of the AR.Drone. Unfortunately this position is only available with a delay because of the WLAN transmission between the AR.Drone and the controlling device. The delay decreases the precision of the position estimation and therefore, we decided to use a discrete Kalaman filter to estimate the position at the current time. Our implementation of the discrete Kalman filter takes the different measurements from the past and the current control inputs to make an estimation of the actual position. Kalman filtering has wide-spread control-applications and uses a recursive algorithm which works in a two step process.

Year:

2013
Type of Publication:

(16)Semester Group Work
Supervisor:

S. M. Huck

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