Machine vision system errors for unmanned aerial vehicle navigation

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

  • Lars Lindner
  • Oleg Sergiyenko
  • Moises Rivas-Lopez
  • Mykhailo Ivanov
  • Julio C. Rodriguez-Quinonez
  • Daniel Hernandez-Balbuena
  • Wendy Flores-Fuentes
  • Vera Tyrsa
  • Fabian N. Muerrieta-Rico
  • Paolo Mercorelli

The use of laser scanners as machine vision systems in Unmanned Aerial Vehicle (UAV) navigation offers a wide range of advantages, when compared with camera-based systems. As one advantage, the measurement of real physical distances can be mentioned, which results in a reduction of measurement times and thereby fast image processing of the UAV surrounding medium. In previous work, a novel laser scanner namely Technical Vision System (TVS) was presented, which implements a continuous laser scan for determination of 3D coordinates of any object under observation. Also previous work has shown the advantage, when using high-quality instead of low-quality DC motors as actuators for positioning the laser ray in the TVS field-of-view. However, the static friction in the ball bearings of the motor shaft leads to a residual error not zero for the angular error in steady state. Present paper introduces a new approach of estimating this residual error by use of a friction model. Thereby, the friction model is described and used for simulation of the residual angular error when controlling the DC motor in open-loop configuration and validated by experimentation results.

OriginalspracheEnglisch
TitelProceedings : 2017 IEEE International Symposium on Industrial Electronics (ISIE)
Anzahl der Seiten6
VerlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum03.08.2017
Seiten1615-1620
ISBN (elektronisch)978-1-5090-1412-5
DOIs
PublikationsstatusErschienen - 03.08.2017
VeranstaltungInternational Symposium on Industrial Electronics - ISIE 2017 - Edinburgh, Großbritannien / Vereinigtes Königreich
Dauer: 19.06.201721.06.2017
Konferenznummer: 26
http://www.isie2017.org/

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