A computer vision assisted system for autonomous forklift vehicles in real factory environment
學年 105
學期 1
出版（發表）日期 2016-11-23
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 Chiang, Jen-shiun;Li, Shih-an
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 en_US
ISSN 1573-7721
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 否
國別 NLD
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118487 )

SDGS 產業創新與基礎設施