Orchard navigation using derivative free Kalman filtering

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Abstract

This paper describes the use of derivative free filters for mobile robot localization and navigation in an orchard. The localization algorithm fuses odometry and gyro measurements with line features representing the surrounding fruit trees of the orchard. The line features are created on basis of 2D laser scanner data by a least square algorithm. The three derivative free filters are compared to an EKF based localization method on a typical run covering four rows in the orchard. The Matlab R toolbox Kalmtool is used for easy switching between different filter implementations without the need for changing the base structure of the system.
Original languageEnglish
Title of host publicationProceedings of the American Control Conference 2011
PublisherAACC
Publication date2011
Pages4679-4684
ISBN (Print)978-1-4577-0080-4
Publication statusPublished - 2011
Event2011 American Control Conference - San Francisco, CA, United States
Duration: 29 Jun 20111 Jul 2011
http://a2c2.org/conferences/acc2011/index.php?r=1&page=Greetings&w=1280&b=2

Conference

Conference2011 American Control Conference
CountryUnited States
CitySan Francisco, CA
Period29/06/201101/07/2011
Internet address
SeriesAmerican Control Conference
ISSN0743-1619

Keywords

  • Autonomous mobile robots
  • Sensor fusion
  • State estimation
  • Robot navigation
  • Localization

Cite this

Hansen, S., Bayramoglu, E., Andersen, J. C., Ravn, O., Andersen, N. A., & Poulsen, N. K. (2011). Orchard navigation using derivative free Kalman filtering. In Proceedings of the American Control Conference 2011 (pp. 4679-4684). AACC. American Control Conference