@inproceedings{5b4dd6c7c79d4b09a24ab166ea83b325,
title = "Robotic arm object detection system",
abstract = "Most of the automation technology in today's factories produces fixed products over fixed production lines; this is called fixed automation. However, many companies today have short product cycles, many product varieties, and small batch sizes, and so fixed automation is not a practical solution. Therefore, our research team aims to develop a smart robotic arm system that can work in flexible automation. Towards that goal, this article describes an innovative gripping system for the screwdriver. The screwdriver gripping system uses faster region-based convolutional network to detect the gripping target, and it uses image processing methods to find the best gripping point of the object; the next command then gives the arm its control decision.",
keywords = "Deep learning, Flexible automation, Image processing",
author = "Perng, {Jau Woei} and Wang, {Chiao Sheng} and Tsai, {Yun Chu} and Chang, {Yu Cheng}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference on Artificial Intelligence for Industries, AI4I 2019 ; Conference date: 25-09-2019 Through 27-09-2019",
year = "2019",
month = sep,
doi = "10.1109/AI4I46381.2019.00026",
language = "English",
series = "Proceedings - 2019 2nd International Conference on Artificial Intelligence for Industries, AI4I 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "75--78",
booktitle = "Proceedings - 2019 2nd International Conference on Artificial Intelligence for Industries, AI4I 2019",
address = "美國",
}