A calibration method is proposed for six-DoF serial robot based on multiple identification spaces consisting of two subspaces in which the orientations of joint 3 and poses of end-effector are measured simultaneously using hybrid sensors. The rotational geometric errors with higher sensitivities are identified in the first space while the rest are identified in the second. Compared with single identification space used in traditional methods, the number of geometric errors to be identified is reduced in each subspace. Thus the identification vectors corresponding to the geometric errors belonging to identification models can be better spaced. Simulation results show that the observability indices and identifiability are further improved by using the multiple identification spaces. Experimental results are also obtained from a six-DoF serial robot with laser tracker and IMUs to verify the identification accuracy improvement. Uncertainty analysis of each identification results is also provided.

中文翻译：

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基于多个识别空间的机器人标定的可观察性指标优化

提出了一种六自由度串行机器人的标定方法，该方法基于由两个子空间组成的多个识别空间，其中使用混合传感器同时测量关节3的方向和末端执行器的姿势。在第一个空间中识别出具有较高灵敏度的旋转几何误差，而在第二个空间中识别出其余空间。与传统方法中使用的单个识别空间相比，每个子空间中要识别的几何错误数量有所减少。因此，对应于属于识别模型的几何误差的识别向量可以被更好地间隔。仿真结果表明，利用多个识别空间可以进一步提高可观察性指标和可识别性。还从具有激光跟踪器和IMU的六自由度串行机器人获得了实验结果，以验证识别精度的提高。还提供了每个鉴定结果的不确定性分析。