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Simultaneous and on-line calibration of a robot-based inspecting system

机译:基于机器人的检查系统的同时在线校准

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摘要

For a robot-based inspecting system calibration procedure in the production environment, it is desirable that the calibration technique should be automatic, time-saving and convenient to implement. The paper presents a new self-calibration method to calibrate and compensate for the robot-based inspecting system's kinematic errors. Compared with traditional calibration methods, this calibration approach has several unique features. First, the inspecting system can be calibrated without external measurement devices since an optical sensor is mounted to the robot end-effector as its integral part, so it can make the inspecting system realizing on-line calibration. Second, it simultaneously calibrates all the kinematic parameters of the inspecting system in one step to avoid error propagation rather than calibrate the hand-eye relationship, the robot itself and the robot exterior relationship separately. Third, the paper analyzes and eliminates redundant kinematic parameters in the inspecting system's kinematic model and derives a MDH model without redundancy. These features not only realize the automatic calibration of the inspecting system but also greatly reduce the number of identified parameters and avoid error propagation, therefore, enhance the efficiency and accuracy of parameter estimation. Experiments are conducted on a 6 DOF serial robot-based inspecting system to validate the good performance of the proposed method.
机译:对于生产环境中的基于机器人的检查系统校准程序,期望校准技术应该是自动的,省时的并且易于实施。本文提出了一种新的自校准方法,以校准和补偿基于机器人的检查系统的运动学误差。与传统的校准方法相比,此校准方法具有几个独特的功能。首先,由于光学传感器作为其整体部分安装在机器人末端执行器上,因此无需外部测量设备即可对检查系统进行校准,因此可以使检查系统实现在线校准。其次,它一步一步地校准了检查系统的所有运动学参数,以避免误差传播,而不是分别校准手眼关系,机器人本身和机器人外部关系。第三,本文分析并消除了检查系统运动模型中的冗余运动参数,并得出了无冗余的MDH模型。这些特征不仅实现了检测系统的自动校准,而且大大减少了所识别参数的数量,避免了误差的传播,从而提高了参数估计的效率和准确性。在基于六自由度串行机器人的检测系统上进行了实验,以验证所提出方法的良好性能。

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