识别结果表明，约束变尺度方法不仅具有较高的计算精度和良好的数值稳定性，并且具有一定的抑制数据噪音的能力。
The results showed that the restraint variable-dimension method not only could have high calculation accuracy and good numeric stability but also have certain data noise control capability.
通过实例分析显示，它具有比约束变量轮换法更高的计算精度和稳定性。
Several examples showed that this improved method has more calculated precision and stability than constrained cyclic variable method.
为了提高并联机器人运动精度，提出了一种利用姿态约束的运动学标定方法。
A new calibration method using orientation constraint is presented to improve the accuracy of parallel robots.
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