Derivative free Kalman filtering used for orchard navigation

Author

Hansen, S. ; Bayramoglu, E. ; Andersen, J.C. ; Ravn, O. ; Andersen, N.A. ; Poulsen, Niels Kjolstad

Author_Institution

Dept. of Electr. Eng., Tech. Univ. of Denmark, Lyngby, Denmark

fYear

2010

fDate

26-29 July 2010

Firstpage

1

Lastpage

8

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® toolbox Kalmtool is used for easy switching between different filter implementations without the need for changing the base structure of the system.

Keywords

Kalman filters; agricultural machinery; agricultural products; distance measurement; industrial robots; least squares approximations; mobile robots; path planning; sensor fusion; 2D laser scanner; Matlab toolbox Kalmtool; autonomous tractor; derivative free Kalman filtering; fruit tree; gyro measurement; least square algorithm; line feature; localisation algorithm; mobile robot localisation; odometry measurement; orchard environment; orchard navigation; sensor fusion; Agricultural machinery; Approximation methods; Equations; Kalman filters; Mathematical model; Robot sensing systems; Autonomous mobile robots; Localisation; Robot navigation; Sensor fusion; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Fusion (FUSION), 2010 13th Conference on

Conference_Location

Edinburgh

Print_ISBN

978-0-9824438-1-1

Type

conf

DOI

10.1109/ICIF.2010.5712041

Filename

5712041