Abstract

This work addresses the problem of the global localization of a mobile robot by exploiting RFID technology. The robot is equipped with kinematic sensors capable of measuring the incremental distances covered by each wheel and an RFID reader which measures the phase of the signal that is backscattered by reference RFID tags situated inside the environment at known positions. The motion of the robot with respect to the tags enables the collection of measurements from multiple antenna-locations, in a synthetic-aperture sense. Localization of the mobile robot over time is accomplished by processing short segments of trajectory during each iteration. The odometry-data are exploited to estimate each segment of the vehicle’s trajectory relative to an unknown initial position. The odometry-based estimation, the known positions of the reference tags, the unwrapped phase measurements and a phase-to-distance model represent the input to a data-fit problem, the solution of which reveals the unknown initial position and orientation of the trajectory segment in the absolute frame. Thanks to phase unwrapping, the data-fit problem features convexity-type properties and the solution is rapidly found by non-linear optimization techniques. The influence of different algorithmic features on the performance of the method is investigated in a simulative context. An experimental campaign that employs a prototype robotic agent equipped with two antennas reports a mean absolute localization error of less than 0.1m, while the execution time stays below the measurements’ collection-time such that the real-time capability of the method is preserved.

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