基于Webots的视觉引导工业机器人分拣系统设计

Yunlong Pan, Xing Ma, C. Mu, Haiping An, Jianyu Chen
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引用次数: 2

摘要

针对工业生产线人工检测效率低的问题,本文构建了基于Webots的视觉导视分拣系统仿真平台。对于静态目标工件,由摄像机采集图像,利用Hu不变矩快速识别,并借助链码进一步识别,使分拣任务由机器人完成。对于动态目标工件,图像处理时间较长。会有跟踪滞后现象。利用卡尔曼滤波预测位置,实现对目标的跟踪。实验结果表明,在形状质心特征和跟踪误差在2个像素以内的情况下,该系统可以在输送机0.2Sm/s的速度下实现目标检测和跟踪,并且具有较好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Industrial Robot Sorting System with Visual Guidance Based on Webots
Aiming at the low efficiency of artificial detection in industrial production line, this paper builds a simulation platform of visual guide sorting system based on Webots. For static target work pieces, image is captured by the camera, use Hu invariant moments quick recognition, and get the help of chain code to further identify, so that the sorting task can be done by robots. For dynamic target work pieces, it takes much time to process the image. There will be a tracking lag phenomenon. Using Kalman filter to predict the position, we can track the target. Experimental results showed that, with the feature in the centroid of shape and the tracking error in two pixels or less, the system could achieve target-detecting and tracking at the 0.2Sm/s speed of conveyor, as well as have a better robustness.
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