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Complementary Vision based Data Fusion for Robust Positioning and Directed Flight of an Autonomous Quadrocopter

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-113621
  • 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 rateThe 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.zeige mehrzeige weniger

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Metadaten
Autor(en): Nils Gageik, Eric Reinthal, Paul Benz, Sergio Montenegro
URN:urn:nbn:de:bvb:20-opus-113621
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Mathematik und Informatik / Institut für Informatik
Sprache der Veröffentlichung:Englisch
Erscheinungsjahr:2014
Originalveröffentlichung / Quelle:International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 5, No. 5, September 2014. DOI : 10.5121/ijaia.2014.5501
DOI:https://doi.org/10.5121/ijaia.2014.5501
Allgemeine fachliche Zuordnung (DDC-Klassifikation):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Freie Schlagwort(e):Autonomous UAV; Data Fusion; Directed Flight; Positioning; Quadrocopter; Quadrotor; Vision Based
Datum der Freischaltung:22.06.2015
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2014
Lizenz (Deutsch):License LogoDeutsches Urheberrecht