@inproceedings{1266543ec1aa4cc7847ab11d2964cc5e,
title = "An Automatic Robotic End-Effector System Based on Visual Detection",
abstract = "According to the problem that a traditional end-effector is fixed to the wrist of a robotic arm and cannot be replaced autonomously, this paper designs a robotic end-effector system that can perform multiple tasks for manipulation robots. The system consists of a tool changer and three operating tools. The advantage of the end-effector is that the motor driving module of operating tools is reduced, and the driving torque is provided by the tool changer. So the size and weight of the operating tool are small and the structure is simple. In order to realize autonomous tool change, a new visual identification marker is designed. A new grasping data set is collected and a hierarchical encoder-decoder neural network is also proposed. The experimental results demonstrate the feasibility of the design method.",
keywords = "Robotic end-effector, Tool changer, Visual detection",
author = "Junyuan Tao and Bin Wang and Shuai Yang and Qifan Duan and Baoxu Feng",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 18th Chinese Intelligent Systems Conference, CISC 2022 ; Conference date: 15-10-2022 Through 16-10-2022",
year = "2022",
doi = "10.1007/978-981-19-6226-4\_79",
language = "英语",
isbn = "9789811962257",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "828--838",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Shoujun Zhao",
booktitle = "Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II",
address = "德国",
}