作者
Qun Ma, Jianwei Niu, Zhenchao Ouyang, Mo Li, Tao Ren, QingFeng Li
发表日期
2020/8/1
研讨会论文
2020 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2020 6th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)
页码范围
246-251
出版商
IEEE
简介
Industrial robots are widely used in current production lines, and complex pipeline processes, especially those with different assembly requirements, are designed for intelligent manufacturing in the era of industry 4.0. During the new crown epidemic, a large number of car companies used the production line to transform production of medical materials such as masks and protective clothing, which provided a strong guarantee for fighting the epidemic. In this scenario, a pipeline is often assembled from robotic arms from multiple suppliers. The traditional methods is complex and takes a lot of time. In this paper, we propose a novel deep learning based robot arm 3D pose estimation and calibration model with simple Kinect stereo cameras which can be deployed on light-weight edge computing systems. The light-weight deep CNN model can detection 5 predefined key points based on RGB-D data. In this way, when …
引用总数
20202021202220231121
学术搜索中的文章
Q Ma, J Niu, Z Ouyang, M Li, T Ren, QF Li - 2020 7th IEEE International Conference on Cyber …, 2020