{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,19]],"date-time":"2025-01-19T05:17:05Z","timestamp":1737263825020,"version":"3.33.0"},"reference-count":24,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2007,3,13]],"date-time":"2007-03-13T00:00:00Z","timestamp":1173744000000},"content-version":"vor","delay-in-days":4819,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Robotic Syst."],"published-print":{"date-parts":[[1994,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A model\u2010based approach to determining the location of an automated guided vehicle (AGV) in the navigation session is proposed. Significant scenes along the navigation path are taken and stored as model images. Also, specific templates of each model image are chosen in advance for matching. When the AGV approaches one significant scene in the navigation session, an input image is taken and the corresponding model image is fetched. Each template in the model image is matched with the input image through the use of the three\u2010step method. The templates are directly used for matching; therefore, no special image processing techniques are required for the input image in the navigation session. In addition, several templates in a model image are used for matching instead of the model image itself. This promotes the robustness of the matching results and saves the computation cost. Furthermore, the 2D string method is used as a post\u2010verifier to discard erroneous matching results. The remaining correct matching results then can be used to determine the vehicle location on the navigation path. Simulated experiments are implemented and the results confirm the feasibility of the proposed approach. \u00a9 1994 John Wiley &amp; Sons, Inc.<\/jats:p>","DOI":"10.1002\/rob.4620110305","type":"journal-article","created":{"date-parts":[[2007,7,6]],"date-time":"2007-07-06T14:25:29Z","timestamp":1183731929000},"page":"181-195","source":"Crossref","is-referenced-by-count":10,"title":["Model\u2010based location of automated guided vehicles in the navigation sessions by 3d computer vision"],"prefix":"10.1002","volume":"11","author":[{"given":"Pai\u2010Shih","family":"Lee","sequence":"first","affiliation":[]},{"given":"Yuh\u2010Erl","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Ling\u2010Ling","family":"Wang","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2007,3,13]]},"reference":[{"key":"e_1_2_1_2_2","unstructured":"L. L.WangandW. H.Tsai \u201cCar safety driving aided by 3\u2010D image analysis techniques \u201d Proc. of Microelectronics and Information Science and Technology Workshop Hsinchu Taiwan September1986 pp.687\u2013701."},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/JRA.1986.1087052"},{"key":"e_1_2_1_4_2","doi-asserted-by":"crossref","unstructured":"I. J.Cox \u201cBlanche: An autonomous robot vehicle for structured environments \u201d Proc. IEEE Int. Conf. on Robotics and Automation Philadelphia PA 1988 pp.978\u2013982.","DOI":"10.1109\/ROBOT.1988.12187"},{"key":"e_1_2_1_5_2","doi-asserted-by":"crossref","unstructured":"T.Tsumura \u201cSurvey of autonomous guided vehicle in Japanese factory \u201d Proc. IEEE Int. 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