Rotation-Based Dynamic Localization at an Initial Dead-Zone Avoidance Stage on an RFID Tag Lattice

Abstract

We have developed a novel way for robots to estimate their pose dynamically in an environment in which RFID tags have been arranged. We previously developed a method for localizing robots using a particle filter. Testing in a room equipped with an RFID tag lattice at 300-mm intervals revealed that the estimation fails when the robot’s RFID readers are near the center of the robot’s rotation since the reader could not detect enough tags depending on the robot’s rotating location. We overcame this problem by developing an active localization algorithm that generates an entropy map from RFID tag arrangement information, predicts the pose using a particle filter, and attracts the robot to the target using a dynamic model whose basic unit is rotation-based angular velocity. Testing demonstrated that a robot using this algorithm and an entropy map can estimate its pose robustly without falling into a dead zone by moving only about 200 mm.