教師資料查詢 | 類別: 期刊論文 | 教師: 江正雄 CHIANG JEN-SHIUN (瀏覽個人網頁)

標題:A computer vision assisted system for autonomous forklift vehicles in real factory environment
學年106
學期1
出版(發表)日期2017/09/01
作品名稱A computer vision assisted system for autonomous forklift vehicles in real factory environment
作品名稱(其他語言)
著者Jia-Liang Syu; Hsin-Ting Li; Jen-Shiun Chiang; Chih-Hsien Hsia*; Po-Han Wu; Chi-Fang Hsieh; Shih-An Li
單位
出版者
著錄名稱、卷期、頁數Multimedia Tools and Applications 76(18), p.18387-18407
摘要Industry 4.0 is an important trend in factory automation nowadays. Among the Automated-Storage-and-Retrieval-System (ASRS) is one of the most important issues for industry. It is widely used in a variety of industries for a variety of storage applications in factories and warehouses. However, the cost of constructing an ASRS is so high that most small/medium enterprises cannot afford it. A forklift system is a cheaper alternative to a complicated ASRS. In this work, a new pallet detection method that uses an Adaptive Structure Feature (ASF) and Direction Weighted Overlapping (DWO) ratio to allow forklifts to pick up a pallet is proposed, using a monocular vision system on the forklift. Combining the ASF and DWO ratio for pallet detection, the proposed method removes most of the non-stationary (dynamic) background and significantly increases the processing efficiency. A Haar like-based Adaboost scheme uses an AS for pallets algorithm to detect pallets. It detects the pallet in a dark environment. Finally, by calculating the DWO ratio between the detected pallets and tracking records, it avoids erroneous candidates during object tracking. Therefore, this work improves the pallet detection to solve the problem with an effective design. As results show that the hybrid algorithms that are proposed in this work increase the average pallet detection rate by 95 %.
關鍵字Industry 4.0;Automated storage and retrieval systems;Forklift;Adaboost;Pallet detection
語言英文(美國)
ISSN
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度
國別美國
公開徵稿
出版型式,紙本
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