Localization of mobile robots: Development and comparative evaluation of algorithms based on odometric and inertial sensors

An autonomous mobile robot must be able to elaborate the measures provided by the sensor equipment to localize itself with respect to a coordinate system. The precision of the location estimate depends on the sensor accuracy and on the reliability of the measure processing algorithm. The purpose of this article is to propose a low cost positioning system using internal sensors like odometers and optical fiber gyroscopes. Three simple localization algorithms based on different sensor data processing procedures are presented. Two of them operate in a deterministic framework, the third operates in a stochastic framework where the uncertainty is induced by sensing and unmodeled robot dynamics. The performance of the proposed localization algorithms are tested through a wide set of laboratory experiments and compared in terms of localization accuracy and computational cost