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Sensor Fusion of Odometer, Compass and Beacon Distance for Mobile Robots
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Author(s): Rufus Fraanje (The Hague University of Applied Sciences, Delft, Netherlands), René Beltman (Lely, Maassluis, Netherlands), Fidelis Theinert (The Hague University of Applied Sciences, Delft, Netherlands), Michiel van Osch (Fontys University of Applied Sciences, Eindhoven, Netherlands), Teade Punter (Fontys University of Applied Sciences, Eindhoven, Netherlands)and John Bolte (The Hague University of Applied Sciences, Delft, Netherlands)
Copyright: 2020
Volume: 10
Issue: 1
Pages: 17
Source title:
International Journal of Artificial Intelligence and Machine Learning (IJAIML)
Editor(s)-in-Chief: Maki K. Habib (The American University in Cairo, Egypt)
DOI: 10.4018/IJAIML.2020010101
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Abstract
The estimation of the pose of a differential drive mobile robot from noisy odometer, compass, and beacon distance measurements is studied. The estimation problem, which is a state estimation problem with unknown input, is reformulated into a state estimation problem with known input and a process noise term. A heuristic sensor fusion algorithm solving this state-estimation problem is proposed and compared with the extended Kalman filter solution and the Particle Filter solution in a simulation experiment.
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