RSS-based Robot Localization in Critical Environments using Reservoir Computing
Mauro Dragone, Claudio Gallicchio, Roberto Guzmán, Alessio Micheli · CINECA IRIS Institutial research information system (University of Pisa) · 2016
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.