Efficient Failure Detection for Mobile Robots Using Mixed-Abstraction Particle Filters View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2006-03-09

AUTHORS

Christian Plagemann , Cyrill Stachniss , Wolfram Burgard

ABSTRACT

In this paper, we consider the problem of online failure detection and isolation for mobile robots. The goal is to enable a mobile robot to determine whether the system is running free of faults or to identify the cause for faulty behavior. In general, failures cannot be detected by solely monitoring the process model for the error free mode because if certain model assumptions are violated the observation likelihood might not indicate a defect. Existing approaches therefore use comparably complex system models to cover all possible system behaviors. In this paper, we propose the mixed-abstraction particle filter as an efficient way of dealing with potential failures of mobile robots. It uses a hierarchy of process models to actively validate the model assumptions and distribute the computational resources between the models adaptively. We present an implementation of our algorithm and discuss results obtained from simulated and real-robot experiments. More... »

PAGES

93-107

Book

TITLE

European Robotics Symposium 2006

ISBN

978-3-540-32689-2
978-3-540-32689-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11681120_8

DOI

http://dx.doi.org/10.1007/11681120_8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012715368


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