This paper proposes a new calibration method for joint-dependent geometric errors of six-DoF industrial robots. Chebyshev polynomials are adopted to characterize the high-order joint-dependent geometric error model, revealing the impact of strain wave gearing errors and other sources more accurately. This effort also brings higher observability index on condition of an appropriate order. Furthermore, the geometric errors are lumped into different groups according to different sensitivities and the corresponding identification models are also established. In this way, each identification subspace contains much fewer error parameters with similar sensitivity. The simulations prove that better measurement configurations can be acquired using the proposed method according to the evaluation of observability indices. For implementation, sensor systems are designed to be fixed on joint 3 and joint 6 respectively to establish the multiple identification spaces. Alternative strategy for the robot without mechanical interface on joint 3 is also provided. Based on this, a set of real calibrations are performed and the results with joint-dependent models and multiple identification spaces indicate better identification accuracies.

针对六自由度工业机器人的关节相关几何误差，提出了一种新的标定方法。Chebyshev多项式用于表征高阶关节相关几何误差模型，从而更准确地揭示了应变波齿轮误差和其他来源的影响。在适当顺序的情况下，这种努力还带来了更高的可观察性指数。此外，根据不同的灵敏度将几何误差归为不同的组，并建立了相应的识别模型。这样，每个标识子空间都包含更少的具有相似灵敏度的错误参数。仿真结果表明，根据可观测性指标的评估，使用所提出的方法可以获得更好的测量配置。为了实施，传感器系统设计为分别固定在关节3和关节6上，以建立多个标识空间。还提供了在关节3上没有机械接口的机器人的替代策略。基于此，将执行一组真实的校准，并且具有关节相关模型和多个标识空间的结果表明具有更好的标识准确性。