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Finding the Kinematic Base Frame of a Robot by Hand-Eye Calibration Using 3D Position Data

机译:使用3D位置数据通过手眼校准找到机器人的运动学基础框架

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When a robot is required to perform specific tasks defined in the world frame, there is a need for finding the coordinate transformation between the kinematic base frame of the robot and the world frame. The kinematic base frame used by the robot controller to define and evaluate the kinematics may deviate from the mechanical base frame constructed based on structural features. Besides, by using kinematic modeling rules such as the product of exponentials (POE) formula, the base frame can be arbitrarily located, and does not have to be related to any feature of the mechanical structure. As a result, the kinematic base frame cannot be measured directly. This paper proposes to find the kinematic base frame by solving a hand-eye calibration problem using 3D position measurements only, which avoids the inconvenience and inaccuracy of measuring orientations and thus significantly facilitates practical operations. A closed-form solution and an iterative solution are explicitly formulated and proved effective by simulations. Comprehensive analyses of the impact of key parameters to the accuracy of the solution are also carried out, providing four guidelines to better conduct practical operations. Finally, experiments on a 7-DOF industrial robot are performed with an optical tracking system to demonstrate the superiority of the proposed method using position data only over the method using full pose data.
机译:当要求机器人执行世界框架中定义的特定任务时,需要找到机器人的运动学基础框架与世界框架之间的坐标变换。机器人控制器用来定义和评估运动学的运动学基础框架可能会偏离基于结构特征构造的机械学基础框架。此外,通过使用诸如指数乘积(POE)公式之类的运动学建模规则,可以任意定位基础框架,并且不必与机械结构的任何特征相关。结果,不能直接测量运动基础框架。本文提出通过仅使用3D位置测量来解决手眼校准问题来找到运动学基础框架,从而避免了测量方向的不便和不准确,从而极大地方便了实际操作。明确制定了封闭形式的解决方案和迭代解决方案,并通过仿真证明了其有效性。还对关键参数对解决方案准确性的影响进行了综合分析,为更好地进行实际操作提供了四项准则。最后,使用光学跟踪系统在7自由度工业机器人上进行实验,以证明所提出的仅使用位置数据的方法优于使用完整姿态数据的方法。

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