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Evaluation of Kinect Vision Sensor for Bin-Picking Applications: Improved Component Separation Accuracy with Combined Use of Depth Map and Color Image

机译:用于宾馆拣选应用的Kinect Vision传感器的评估:改进了组件分离精度,综合使用深度图和彩色图像

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This report describes a problem involved with use of Kinect depth maps for robot picking of randomly stacked components, and also a solution to this problems. When Kinect is installed above stacked parts and processing is performed using only the obtained Kinect depth map information, there are cases when individual small metal components cannot be separately identified. So that the robot can reliably pick up a single component in these cases, this report demonstrates that in areas where the system incorrectly identifies multiple components as a single component, the addition of color image information and blob analysis of the color image results in accurate separation of the individual components, allowing a single item to be identified for picking.
机译:本报告描述了使用Kinect Depth Maps用于随机堆叠组件的机器人拣选的使用,以及解决这一问题的解决方案。 当Kinect安装在上面的堆叠部件上方并且仅使用所获得的Kinect深度图信息执行处理时,存在不能单独识别单个小金属部件时的情况。 因此,机器人可以在这些情况下可靠地拾取单个组件,本报告说明,在系统错误地将多个组件识别为单个组件的区域中,彩色图像信息和彩色图像的BLOB分析会导致精确的分离 各个组件,允许识别单个项目进行拣选。

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