移動機器人融合主動式RFID和雷射掃描器之定位

Localization of an Autonomous Mobile Robot by Fusing Active RFID and Ranging Laser Scanner

林鴻興(Hung-Hsing Lin) ； 蔡清池(Ching-Chih Tsai)

《修平學報》 22期 (2011/03) Pp. 1-18

https://doi.org/10.29548/BGYY.201103.0001

摘要

本文目的是發展出整合主動式無線射頻辨識系統(RFID)、里程計和雷射掃描器等感測系統的室內移動機器人(AMR)全域姿態定位方法。
首先探討主動式定位系統是從選擇的電子標籤到讀取器之間所接收到發射訊號強度數據轉換的距離，利用即時最小平方演算法，可估測出機器人在起動時的未知位置和方位角姿態初值。最後在任何環境中，主動式無線射頻辨識系統利用即時最小平方法，並融合雷射掃描器使用模糊增廣訊息濾波策略，可以估測移動機器人全域姿態。並透過實驗結果，證實本文所提之定位系統是有效性可行的。

關鍵字

增廣訊息濾波器 ； 雷射掃描器 ； 定位 ； 無線射頻辨識系統 ； 感測器融合

並列摘要

The purpose of this paper aims at developing a global pose localization method for an autonomous mobile robot (AMR) in indoor environments by fusing measurements including an active radio frequency identification device (RFID), one odometric device, and a ranging laser scanner.
First, to explore the distance from transpose of signal intensity between receive and transmit from selected tags of a reader. Use a real-time least-square method to estimate the unknown position and orientation when the mobile robot start-up. Last, use fuzzy extended information filtering (FEIF) scheme of RFID with real-time least-sequence method fuse laser scanner to estimate global pose of a mobile robot moving in any circumstance. Experimental results are provided to show the effectiveness and merits of the proposed localization systems.

並列關鍵字

Extended Information Filter ； Laser Scanner ； Localization ； RFID ； Sensor Fusion

參考文獻

B. Graf, M. Hans, and R. D. Schraft, “Mobile robot assistants,” IEEE Robotics and Automation Magzine, vol. 11, no.2, pp.67-77, 2004.

P. S. Maybeck, Stochastic Models, Estimation, and Control, vol.1, New York, Academic Press, 1979.

H. H. Lin, C. C. Tsai, J. C. Hsu, “Ultrasonic localization and pose tracking of an autonomous mobile robot via fuzzy adaptive extended information filtering,” IEEE Transactions on Instrumentation and Measurement, vol. 57, no.9, pp.2024-2034,2008.

S. Se, D. G. Lowe, and J. J. Little, “Vision-based global localization and mapping for mobile robots,” IEEE Transactions Robotics and Automation, vol. 21, no. 3, pp. 364-375, 2005.

David C. K. Yuen, Bruce A. MacDonald, “Vision-based localization algorithm based on landmark matching, triangulation, reconstruction, and comparison,” IEEE Transactions on robotics, vol. 21, no. 2-3, pp. 217-221, 2005.