A Multiview Recognition Method of Predefined Objects for Robot Assembly Using Deep Learning and Its Implementation on an FPGA
ELECTRONICS(2022)
摘要
The process of recognizing manufacturing parts in real time requires fast, accurate, small, and low-power-consumption sensors. Here, we describe a method to extract descriptors from several objects observed from a wide range of angles in a three-dimensional space. These descriptors define the dataset, which allows for the training and further validation of a convolutional neural network. The classification is implemented in reconfigurable hardware in an embedded system with an RGB sensor and the processing unit. The system achieved an accuracy of 96.67% and a speed 2.25x faster than the results reported for state-of-the-art solutions. Our proposal is 655 times faster than implementation on a PC. The presented embedded system meets the criteria of real-time video processing and it is suitable as an enhancement for the hand of a robotic arm in an intelligent manufacturing cell.
更多查看译文
关键词
robot vision, FPGA, CNN, object detection, hardware implementation, LeNET-5
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要