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Robotic grasping based on machine vision and SVM

机译:基于机器视觉和SVM的机器人抓取

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Robotic grasping is one of the hot research topics in the field of robotics, which has widely used in many industrial applications. In this study, we proposed a method for robotic grasping based on machine vision and support vector machine algorithm (SVM). A robotic grasping system with a Baxter robot and a Kinect sensor was taken as the research platform. The calibration of eye-to-hand system was completed based on ArUco marker. The grasping rectangle of object was determined based on SVM algorithm. The proposed method was evaluated through experiments by grasping various shape objects. Experimental results showed that the Baxter robot can grasp various shape objects.
机译:机器人抓取是机器人技术领域的热门研究主题之一,已在许多工业应用中得到广泛使用。在这项研究中,我们提出了一种基于机器视觉和支持向量机算法(SVM)的机器人抓取方法。以百特机器人和Kinect传感器组成的机器人抓取系统为研究平台。基于ArUco标记器完成了手对手系统的校准。基于SVM算法确定物体的抓握矩形。通过抓握各种形状的物体,通过实验对提出的方法进行了评估。实验结果表明,Baxter机器人可以抓握各种形状的物体。

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