Supporting both accurate and reliable localization in critical environments is key to increasing the potential of logistic mobile robots. This paper presents a system for indoor robot localization based on Reservoir Computing from noisy radio signal strength index (RSSI) data generated by a network of sensors. The proposed approach is assessed under different conditions in a real-world hospital environment. Experimental results show that the resulting system represents a good trade-off between localization performance and deployment complexity, with the ability to recover from cases in which permanent changes in the environment affect its generalization performance.

RSS-based robot localization in critical environments using reservoir computing

GALLICCHIO, CLAUDIO;MICHELI, ALESSIO
2016-01-01

Abstract

Supporting both accurate and reliable localization in critical environments is key to increasing the potential of logistic mobile robots. This paper presents a system for indoor robot localization based on Reservoir Computing from noisy radio signal strength index (RSSI) data generated by a network of sensors. The proposed approach is assessed under different conditions in a real-world hospital environment. Experimental results show that the resulting system represents a good trade-off between localization performance and deployment complexity, with the ability to recover from cases in which permanent changes in the environment affect its generalization performance.
2016
9782875870278
9782875870278
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/816720
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