9683
2013
eng
article
1
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Waypoint flight parameter comparison of an autonomous UAV
The present paper compares the effect of different waypoint parameters on the flight performance of a special autonomous indoor UAV (unmanned aerial vehicle) fusing ultrasonic, inertial, pressure and optical sensors for 3D positioning and controlling. The investigated parameters are the acceptance threshold for reaching a waypoint as well as the maximal waypoint step size or block size. The effect of these parameters on the flight time and accuracy of the flight path is investigated. Therefore the paper addresses how the acceptance threshold and step size influence the speed and accuracy of the autonomous flight and thus influence the performance of the presented autonomous quadrocopter under real indoor navigation circumstances.
Furthermore the paper demonstrates a drawback of the standard potential field method for navigation of such autonomous quadrocopters and points to an improvement.
International Journal of Artificial Intelligence & Applications (IJAIA)
10.5121/ijaia.2013.4304
urn:nbn:de:bvb:20-opus-96833
In: International Journal of Artificial Intelligence & Applications (IJAIA) (2013) 4: 3, doi:10.5121/ijaia.2013.4304
Nils Gageik
Michael Strohmeier
Sergio Montenegro
eng
uncontrolled
autonomous UAV
eng
uncontrolled
Quadrocopter
eng
uncontrolled
Quadrotor
eng
uncontrolled
waypoint parameter
eng
uncontrolled
navigation
Datenverarbeitung; Informatik
open_access
Institut für Informatik
Förderzeitraum 2013
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/9683/Gageik_ijaia20134304.pdf
9636
2013
eng
article
1
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An Autonomous UAV with an Optical Flow Sensor for Positioning and Navigation
A procedure to control all six DOF (degrees of freedom) of a UAV (unmanned aerial vehicle) without an external reference system and to enable fully autonomous flight is presented here. For 2D positioning the principle of optical flow is used. Together with the output of height estimation, fusing ultrasonic, infrared and inertial and pressure sensor data, the 3D position of the UAV can be computed, controlled and steered. All data processing is done on the UAV. An external computer with a pathway planning interface is for commanding purposes only. The presented system is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application. The focus of this paper is 2D positioning using an optical flow sensor. As a result of the performed evaluation, it can be concluded that for position hold, the standard deviation of the position error is 10cm and after landing the position error is about 30cm.
International Journal of Advanced Robotic Systems
10.5772/56813
urn:nbn:de:bvb:20-opus-96368
In: International Journal of Advanced Robotic Systems (2013) 10: 341, doi:10.5772/56813
Nils Gageik
Michael Strohmeier
Sergio Montenegro
eng
uncontrolled
Autonomous UAV
eng
uncontrolled
Quadrocopter
eng
uncontrolled
Quadrotor
eng
uncontrolled
Optical Flow
eng
uncontrolled
positioning
eng
uncontrolled
navigation
Datenverarbeitung; Informatik
open_access
Institut für Informatik
Förderzeitraum 2013
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/9636/Gageik_56813.pdf
11362
2014
eng
article
1
2015-05-21
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Complementary Vision based Data Fusion for Robust Positioning and Directed Flight of an Autonomous Quadrocopter
The present paper describes an improved 4 DOF (x/y/z/yaw) vision based positioning solution for fully 6 DOF autonomous UAVs, optimised in terms of computation and development costs as well as robustness and performance. The positioning system combines Fourier transform-based image registration (Fourier Tracking) and differential optical flow computation to overcome the drawbacks of a single approach. The first method is capable of recognizing movement in four degree of freedom under variable lighting conditions, but suffers from low sample rate and high computational costs. Differential optical flow computation, on the other hand, enables a very high sample rate to gain control robustness. This method, however, is limited to translational movement only and performs poor in bad lighting conditions. A reliable positioning system for autonomous flights with free heading is obtained by fusing both techniques. Although the vision system can measure the variable altitude during flight, infrared and ultrasonic sensors are used for robustness. This work is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application and makes autonomous directed flight possible.
10.5121/ijaia.2014.5501
urn:nbn:de:bvb:20-opus-113621
International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 5, No. 5, September 2014. DOI : 10.5121/ijaia.2014.5501
Deutsches Urheberrecht
Nils Gageik
Eric Reinthal
Paul Benz
Sergio Montenegro
eng
uncontrolled
Autonomous UAV
eng
uncontrolled
Quadrocopter
eng
uncontrolled
Quadrotor
eng
uncontrolled
Vision Based
eng
uncontrolled
Positioning
eng
uncontrolled
Data Fusion
eng
uncontrolled
Directed Flight
Informatik, Informationswissenschaft, allgemeine Werke
open_access
Institut für Informatik
Förderzeitraum 2014
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/11362/145_Gageik_IJAIA.pdf