{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T18:45:16Z","timestamp":1777488316059,"version":"3.51.4"},"reference-count":17,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2013,8,7]],"date-time":"2013-08-07T00:00:00Z","timestamp":1375833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird\u2019s eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.<\/jats:p>","DOI":"10.3390\/s130810052","type":"journal-article","created":{"date-parts":[[2013,8,7]],"date-time":"2013-08-07T11:46:51Z","timestamp":1375876011000},"page":"10052-10073","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["A Vision-Based Automated Guided Vehicle System with  Marker Recognition for Indoor Use"],"prefix":"10.3390","volume":"13","author":[{"given":"Jeisung","family":"Lee","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang-Ho","family":"Hyun","sequence":"additional","affiliation":[{"name":"Division of Electrical Electronic and Control Engineering, Kongju National University, Cheonan, Chungnam 331-717, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mignon","family":"Park","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,8,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Grewal, M.S., Weill, L.R., and Andrews, A.P. (2007). Global Positioning Systems, Inertial Navigation, and Integration, John Wiley & Sons.","DOI":"10.1002\/0470099720"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0921-8890(99)00085-8","article-title":"Localization and navigation of a mobile robot using natural point landmarks extracted from sonar data","volume":"31","author":"Wijk","year":"2000","journal-title":"Rob. Auton. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Raab, F.H., Blood, E.B., Steiner, T.O., and Jones, H.R. (1979). Magnetic position and orientation tracking system. IEEE Trans. Aerosp. Electron. Syst., 709\u2013718.","DOI":"10.1109\/TAES.1979.308860"},{"key":"ref_4","unstructured":"Kourogi, M., Sakata, N., Okuma, T., and Kurata, T. (2006). 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Robotic Assistance: an Automatic Wheelchair Tracking and Following Functionality by Omnidirectional Vision. Edmonton, AB, Canada.","DOI":"10.1109\/IROS.2005.1545336"},{"key":"ref_13","unstructured":"Sun, Y., Cao, Q., and Chen, W. (2004, January 15\u201319). An Object Tracking and Global Localization Method using Omnidirectional Vision System. Hangzhou, China."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Feng, W., Liu, Y., and Cao, Z. (2008, January 18\u201320). Omnidirectional Vision Tracking and Positioning for Vehicles. Jinan, China.","DOI":"10.1109\/ICNC.2008.737"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1109\/19.231593","article-title":"Two-dimensional position recovery for a free-ranging automated guided vehicle","volume":"42","author":"Petriu","year":"1993","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Kim, G., and Petriu, E.M. (2010, January 6\u20139). 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