Sensor selection by reliability based on possibility measure

Robotic or manufacturing systems become more and more complex for adapting to various environmental conditions. In these systems, sensor fusion methods for estimating states of a system from multiple sensor information have received much attention. Also, it is necessary to select the sensor information for adapting to various situations flexibly. In these days, various methods of fusing multiple information have been proposed so far, but these methods cannot select the sensor information. We propose a sensor selected fusion system using a recurrent neural network. The sensor selection method is based on the production system, considering the reliability calculated by the possibility measure. The effectiveness of the proposed method is shown through a simulation of a mobile robot