Skip to main content

Gitterkartenbasierte Fehlererkennung und Kalibrierung für Umgebungssensoren autonomer mobiler Systeme (AMS)

  • Conference paper
Autonome Mobile Systeme 1996

Part of the book series: Informatik aktuell ((INFORMAT))

Zusammenfassung

Typische Einsatzumgebungen autonomer mobiler Systeme (AMS) [1] zeichnen sich dadurch aus, daß sie nur einen niedrigen Grad an Struktur aufweisen und zudem verschiedene dynamische Objekte (Menschen, andere Fahrzeuge) vorhanden sind. Um sich in seiner Umgebung zurechtzufinden, benötigt das AMS ein Modell, das durch Fusion der Sensormessungen erzeugt wird. Dabei müssen die jeweiligen Unzulänglichkeiten des Meßprinzips sowie der Sensorik selbst (systematische Meßfetiler) berücksichtigt werden [2].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  1. Rencken W.D, Leuthäusser I., Bauer R., Feiten W., Lawitzky G., Möller M., Low-Cost Mobile Robots for Complex Non-Production Environments, Proc. 1st IFAC Int. Workshop on Intelligent Autonomous Vehicles, April 1993.

    Google Scholar 

  2. Beckerman M., Oblow E. M.: Treatment of Systematic Errors in the Processing of Wide-Angle Sonar Sensor Data for Robotic Navigation, IEEE Transactions on Robotics and Automation, vol. 6, No. 2, April 1990.

    Google Scholar 

  3. Borenstein J., Koren Y.: The Vector Field Histogramm — Fast Obstacle Avoidance for Mobile Robots, IEEE Transactions on Robotics and Automation, Vol. 7, No. 3, 1991.

    Google Scholar 

  4. Borenstein J., Koren Y.: Real-Time Obstacle Avoidance for Fast Mobile Robots, IEEE Transactions on Robotics and Automation, Vol. 19, No. 5, 1989.

    Google Scholar 

  5. Matthies L., Elfes A.: Probablistic Estimation Mechanisms and Tesselated Representations for Sensor Fusion, Proceedings of the SPIE — The International Society for Optical Engeneering, Cambridge, MA, USA, 7–9 November 1988.

    Google Scholar 

  6. Elfes A.: Dynamic Control of Robot Perception Using Stochastic Spatial Models, Information Processing in Autonomous Mobile Robots, Proceedings of the International Workshop in Munich, Germany 6–8 March 1991, Springer-Verlag, Germany, 1991.

    Google Scholar 

  7. Elfes A.: Dynamic Control of Robot Perception Using Multi-Property Inference Grids, Proceedings of the 1992 IEEE International Conference on Robotics and Automation, Nice France, May 1992.

    Google Scholar 

  8. Shannon C.E., Weaver W.: The Mathematical Theory of Communication, University of Illinois Press, 1949.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Soika, M. (1996). Gitterkartenbasierte Fehlererkennung und Kalibrierung für Umgebungssensoren autonomer mobiler Systeme (AMS). In: Schmidt, G., Freyberger, F. (eds) Autonome Mobile Systeme 1996. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80324-6_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-80324-6_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61751-8

  • Online ISBN: 978-3-642-80324-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics