Publication: Research - peer-review › Article in proceedings – Annual report year: 2010
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.
|Title||Derivative free Kalman filtering used for orchard navigation|
|Conference||13th International Conference on Information Fusion|
|Period||26/07/10 → 29/07/10|
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