A novel extrinsic calibration method for robotic systems with structured light sensors

Zhichao Cui, Yuehu Liu, Xinzhao Li
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Abstract

The extrinsic calibration for robotic systems with structured light sensor is fundamental to accomplish the tasks of 3D measurement, reverse engineering and quality inspection. In this paper, we proposed a cuboid calibration target with nicks on the surfaces which is easy to extract the control points. In the calibration process, both least square method and the nonlinear optimization based on maximum likelihood criterion are utilized. The degenerate configuration is discussed for non-singularity solution. Both simulation and real data are utilized for robustness test of the algorithm and the experiment shows that the proposed method has 0.6 mm RMS errors of control points. Compared to the existed methods, the proposed method has the advantages of small error, simple operation and high flexibility.
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结构光传感器机器人系统的一种新的外部标定方法
结构光传感器机器人系统的外部标定是完成三维测量、逆向工程和质量检测任务的基础。本文提出了一种易于提取控制点的带有刻痕的长方体标定目标。在标定过程中,采用了最小二乘法和基于极大似然准则的非线性优化方法。讨论了非奇异解的简并构型。利用仿真和实际数据对算法进行鲁棒性检验,实验表明,该方法控制点的均方根误差为0.6 mm。与现有方法相比,该方法具有误差小、操作简单、灵活性高等优点。
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