Using Particle Filter and Machine Learning for Accuracy Estimation of Robot Localization

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Abstract

Robot localization is a fundamental capability of all mobile robots. Because of uncertainties in acting and sensing and environmental factors such as people flocking around robots there is always the risk that a robot loses its localization. Very often behaviors of robots rely on a valid position estimation. Thus, for dependability of robot systems it is of great interest for the system to know the state of its localization component. In this paper we present an approach that allows a robot to asses if the localization is still valid. The approach assumes that the underlying localization approach is based on a particle filter. We use deep learning to identify temporal patterns in the particles in the case of losing/lost localization in combination with weak classifiers from the particle set and perception for boosted learning of a localization monitor. The approach is evaluated in a simulated transport robot environment where a degraded localization is provoked by disturbances cased by dynamic obstacles.
Originalspracheenglisch
TitelAdvances and Trends in Artificial Intelligence. From Theory to Practice
UntertitelIEA/AIE 2019
Redakteure/-innenFranz Wotawa, Gerhard Friedrich, Ingo Pill, Roxane Koitz-Hristov, Moonis Ali
Herausgeber (Verlag)Springer, Cham
Seiten700-713
Seitenumfang14
ISBN (elektronisch)978-3-030-22999-3
ISBN (Print)978-3-030-22998-6
DOIs
PublikationsstatusVeröffentlicht - 15 Jun 2019
Veranstaltung32nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems - Graz, Österreich
Dauer: 9 Jul 201911 Jul 2019

Publikationsreihe

NameLecture Notes in Computer Science
Herausgeber (Verlag)Springer
Band11606

Konferenz

Konferenz32nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems
KurztitelIEA/AIE 2019
LandÖsterreich
OrtGraz
Zeitraum9/07/1911/07/19

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  • Dieses zitieren

    Eder, M. J., Reip, M., & Steinbauer, G. (2019). Using Particle Filter and Machine Learning for Accuracy Estimation of Robot Localization. in F. Wotawa, G. Friedrich, I. Pill, R. Koitz-Hristov, & M. Ali (Hrsg.), Advances and Trends in Artificial Intelligence. From Theory to Practice: IEA/AIE 2019 (S. 700-713). (Lecture Notes in Computer Science; Band 11606). Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_60