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An experimental comparison of localisation methods, the mhl sessions

Steen Savstrup Kristensen, Patric Jensfelt

Year
2004
Citations
20

Abstract

In this paper we compare multi hypothesis localisation (MHL)-which is a mobile robot localisation method based on multi hypothesis tracking - with six other methods reported in the literature. The comparison is performed using a standard set of test data and corresponding evaluation tools, thus facilitating a direct comparison of the obtained results. The experiments show that MHL compares favourably to all other methods in terms of recovering when the robot has been kidnapped. When using a validation gate for filtering out noisy measurements, MHL and the standard extended Kalman filter both perform as well as all other reported methods in terms of accuracy while being faster to compute.

Keywords

Computer scienceKalman filterMobile robotSet (abstract data type)Artificial intelligenceFilter (signal processing)RobotData miningComputer vision

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