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Desensitization of Camera-Aided Manipulation to Target Specification Errors

机译:相机辅助操作对目标规范错误的脱敏

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摘要

Applications of vision-based remotely operated robotic systems range from planetary exploration to hazardous waste remediation. For space applications, where communication time lags are large, the target selection and robot positioning tasks may be performed sequentially, differing from conventional telerobotic maneuvers. For these point-and-move systems, the desired target must be defined in the image plane of the cameras either by an operator or through image processing software. Ambiguity of the target specification will naturally lead to end-effector positioning errors. In this paper, the target specification error covariance is shown to transform linearly to the end-effector positioning error. In addition, a methodology for optimal estimation of camera-view parameters of a vision-based robotic system based on target specification errors is presented. The proposed strategy is based on minimizing the end-effector error covariance matrix. Experimental results are presented demonstrating an increase in end-effector positioning, compared to traditional view parameter estimation by up to 32%.
机译:基于视觉的远程机器人系统的应用范围从行星探测到危险废物修复。对于通信时间滞后较大的空间应用,可以顺序执行目标选择和机器人定位任务,这与常规的遥控机器人操作不同。对于这些点动系统,必须由操作员或通过图像处理软件在摄像机的图像平面中定义所需目标。目标规格的歧义自然会导致末端执行器定位错误。在本文中,目标规格误差协方差显示为线性转换为末端执行器定位误差。另外,提出了一种用于基于目标规范误差来最优估计基于视觉的机器人系统的摄像机视野参数的方法。所提出的策略基于最小化末端执行器误差协方差矩阵。实验结果表明,与传统的视图参数估计相比,末端执行器的位置增加了多达32%。

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