@inproceedings{oai:u-fukui.repo.nii.ac.jp:00022949,
 author = {Takahashi, Yasutake and Ii, Yuta and Jian, Mi and Jun, Wang and Maeda, Yoichiro and Takeda, Masahiko and Nakamura, Ryuji and Miyoshi, Hiroaki and Takeuchi, Hidenori and Yamashita, Yoshinori and Sano, Hiroshi and Masuda, Atsuji},
 book = {IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)},
 month = {Nov},
 note = {This paper presents a self-localization system using multiple RFID reader antennas and High-Frequency RFID-tag textile floor for an indoor autonomous mobile robot. Conventional self-localization systems often use vision sensors and/or laser range finders and an environment model. It is difficult to estimate the exact global location if the environment has number of places that have similar shape boundaries or small number of landmarks to localize. It tends to take a long time to recover the self-localization estimation if it goes wrong at once. Vision sensors work hard in dark lighting condition. Laser range finder often fails to detect distance to a transparent wall. In addition, the self-localization becomes unstable if obstacles occlude landmarks that are important to estimate position of the robot. Door opening and closing condition affects the self- localization performance. Self-localization system based on reading RFID-tags on floor is robust against lighting condition, obstacles, furniture and doors conditions in the environment. Even if the arrangement of the obstacles or furniture in the environment is changed, it is not necessary to update the map for the self-localization. It can localize itself immediately and is free from well-known kidnapped robot problem because the RFID-tags give global po- sition information. Conventional self-localization systems based on reading RFID-tags on floor often use only one RFID reader antenna and have difficulty of orientation estimation. We have developed a self-localization system using multiple RFID reader antennas and High-Frequency RFID-tag textile floor for an indoor autonomous mobile robot. Experimental results show the validity of the proposed methods., 2013 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO) Shibaura Institute of Technology, Tokyo, JAPAN November 7-9, 2013},
 pages = {106--112},
 publisher = {Advanced Robotics and its Social Impacts (ARSO)},
 title = {Mobile Robot Self Localization based on Multi-Antenna-RFID Reader and IC Tag Textile},
 year = {2013}
}