矿用智能机器人抓拍成像技术

Study on the Imaging Technology of Mining Intelligent Robot Snapshot

大块煤矸石在运输过程中卡壳严重易造成设备磨损,为了实现煤炭转载过程中矸石块度大、机器卡壳造成的设备维护时间长、投入大的问题,利用非线性摄影成像模型和K-means聚类算法对智能机器人图像采集和障碍物识别进行了研究,实现了对块度较大煤矸体形状、区域的非线性摄像和特征的准确提取,为智能机器人的应用提供了重要参考,对于解决煤炭转载过程中的问题有现实意义。

Chunks of coal gangue in the course of carriage jam serious easy cause equipment wear and tear,in order to realize the coal transfer in the process of waste rock fragmentation jam,large machine caused by the problem of large equipment maintenance time is long,input,using nonlinear photographic imaging model and K means clustering algorithm for image acquisition and intelligent robot obstacle recognition was studied,and realized with coal waste more body shape,regional characteristics of nonlinear camera and accurate extraction,provides an important reference for the application of intelligent robot,to solve the problems in the process of coal transfer has practical significance.