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Automated 3-D Micrograsping Tasks Performed by Vision-Based Control

机译:基于视觉的控制执行的自动3-D微抓图任务

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We present a fully automated micrograsping methodology that uses a micro-robot and a microgripper to automatically grasp a micropart in three-dimensional (3-D) space. To accurately grasp a micropart in 3-D space, we propose a three-stage micrograsping strategy: (i) coarse alignment of a micropart with a microgripper in the image plane of a video camera system; (ii) alignment of the micropart with the microgripper in the direction normal to the image plane; (iii) fine alignment of the micropart with the microgripper in the image plane, until the micropart is completely grasped. Two different vision-based feedback controllers are employed to perform the coarse and fine alignment in the image plane. The vision-based feedback controller used for the fine alignment employs position feedback signals obtained from two special patterns, which can achieve submicron alignment accuracy. Fully automated micrograsping experiments are conducted on a microassembly robot. The experimental results show that the average alignment accuracy achieved during automated grasping is approximately ${pm 0.07}~mu{rm m}$; the time to complete an automated micrograsping task is as short as 7.9 seconds; and the success rate is as high as 94%.
机译:我们提出了一种全自动的微抓取方法,该方法使用了微型机器人和微型夹具来自动抓住三维(3-D)空间中的微小部分。为了准确地掌握3-D空间中的微零件,我们提出了一个三阶段的微抓握策略:(i)在摄像机系统的图像平面中将微零件与微夹钳进行粗对准; (ii)将微零件与微型夹具在垂直于像平面的方向上对齐; (iii)将微零件与微型夹具在图像平面内精确对齐,直到完全抓住微零件为止。两种不同的基于视觉的反馈控制器用于在图像平面中执行粗调和精调。用于精细对准的基于视觉的反馈控制器采用从两个特殊模式获得的位置反馈信号,可以实现亚微米对准精度。全自动微抓取实验是在微型装配机器人上进行的。实验结果表明,在自动抓取过程中获得的平均对准精度约为$ {pm 0.07}〜mu {rm m} $;完成自动微抓图任务的时间仅为7.9秒;成功率高达94%。

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