Location Recognition Algorithm for Vision-Based Industrial Sorting Robot via Deep Learning
Location Recognition Algorithm for Vision-Based Industrial Sorting Robot via Deep Learning
复制标题
基于深度学习的视觉工业分拣机器人位置识别算法
DOI：
10.1142/s0218001419550097
复制
发表时间：
2019
影响因子：
1.5
通讯作者：
Jinxia Liu
中科院分区：
文献类型：
--
作者：
Xiru Wu;Xingyu Ling;Jinxia Liu
本文将深度卷积神经网络（DCNN）应用于工业生产过程中基于视觉的分拣机器人对复杂工件的自动定位与识别。首先，为了得到工件的位置，提出了像素投影算法（PPA），该算法包括预处理和像素投影运算，消除了光照不均匀，实现了工件图像的定位和分割。然后，通过训练DCNN，得到目标的客观信息并进行识别，用于快速识别工件的合理程度和类型。最后通过实验验证了视觉分拣机器人位置识别算法的有效性。在实验环境下，定位误差和识别精度都得到了明显的改善。
In this paper, the deep convolutional neural network (DCNN) is applied to locating and recognizing complex workpieces automatically for the vision-based sorting robot in industrial production process. Firstly, in order to obtain the location of workpieces, the pixel projection algorithm (PPA), which consists of pre-procession and pixel projection operation, is presented to eliminate uneven illumination, and locate and segment workpieces images. Then, we get the objective information and identify the object by training DCNN, which is used to recognize the rational degree and type of workpieces at a high rate of speed. Finally, experimental results prove the validity of the location-recognition algorithms for the vision-based sorting robot. The location error and recognition accuracy can be significantly improved in the experimental environment.