Abstract
Particle filters have recently gained major attention as a powerful diagnostic tool. Their severe drawback is the computational burden closely related to the number of particles used. Therefore, it is often necessary to work out a compromise between computation time and the quality of results, especially in the case of systems with limited computational resources such as mobile robots. This work outlines the concept of a fault detection and isolation (FDI) system for a mobile robot which is based on a bank of adaptive particle filters and accounts for the aforementioned problems.
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Zając, M. (2011). Adaptive Particle Filter for Fault Detection and Isolation of Mobile Robots. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds) Towards Autonomous Robotic Systems. TAROS 2011. Lecture Notes in Computer Science(), vol 6856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23232-9_35
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DOI: https://doi.org/10.1007/978-3-642-23232-9_35
Publisher Name: Springer, Berlin, Heidelberg
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