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Fault-Tolerant Certainty Grid

World modelling for mobile autonomous robot is usually a process that uses sensor data as input and provides a model of the robot’s environment as output. In this paper we investigate on sensor fusion methods for robustness and fault tolerance. We evaluate three methods according to their performance, memory consumption, and required sensor configurations. The algorithms have been implemented in a four-wheeled autonomous mobile robot that uses a set of three infrared sensors to build the world model. We present a performance analysis of the new algorithms based on simulation and experimental data.