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Among the major shortcomings of modern mobile robot navigation systems are their dependence on an excessive number of sensors and sensor types, and their prohibitively high computational complexity which often requires an additional data processing board to handle it. The present manuscript presents a radio frequency identification (RFID)-based navigation approach where a number of tags are attached at predetermined locations in the environment to guide a robot equipped with an RFID reader in tracking its predefined trajectory. Due to the typical excessive noise characterizing RF signals in general, redundant information extracted from the tags is exploited with the help of a particle swarm optimization (PSO) algorithm to enhance the robotpsilas position approximation accuracy. The effectiveness of the proposed scheme is demonstrated through computer simulations of different testbeds with various complexities.