Derivative free Kalman filtering used for orchard navigation

Søren Hansen (Invited author), Enis Bayramoglu (Invited author), Jens Christian Andersen (Invited author), Ole Ravn (Invited author), Nils Axel Andersen (Invited author), Niels Kjølstad Poulsen (Invited author)

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Abstract

In this paper the use of derivative free filters for mobile robot localisation is investigated. Three different filters are tested on real life data from an autonomous tractor running in an orchard environment. The localisation algorithm fuses odometry and gyro measurements with line features representing the surrounding fruit trees. The line features are created on basis of 2D laser scanner data by a least square algorithm. 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 publicationDerivative free Kalman filtering used for orchard navigation
Publication date2010
ISBN (Print)978-0-9824438-1-1
Publication statusPublished - 2010
Event13th International Conference on Information Fusion - Edinburgh, United Kingdom
Duration: 26 Jul 201029 Jul 2010
http://www.fusion2010.org/

Conference

Conference13th International Conference on Information Fusion
CountryUnited Kingdom
CityEdinburgh
Period26/07/201029/07/2010
Internet address

Cite this

Hansen, S., Bayramoglu, E., Andersen, J. C., Ravn, O., Andersen, N. A., & Poulsen, N. K. (2010). Derivative free Kalman filtering used for orchard navigation. In Derivative free Kalman filtering used for orchard navigation