引用本文: 高文斌, 罗瑞卿, 江自真. 基于局部指数积的模块化机器人运动学参数标定[J]. 机器人, 2021, 43(1): 66-73.
GAO Wenbin, LUO Ruiqing, JIANG Zizhen. Kinematic-Parameter Calibration for Modular Robots Based on the Local POE[J]. ROBOT, 2021, 43(1): 66-73.
 Citation: GAO Wenbin, LUO Ruiqing, JIANG Zizhen. Kinematic-Parameter Calibration for Modular Robots Based on the Local POE[J]. ROBOT, 2021, 43(1): 66-73.

## Kinematic-Parameter Calibration for Modular Robots Based on the Local POE

• 摘要: 针对模块化可重构机器人系统展开基于局部指数积法的运动学参数标定研究，提出一种基于子装配体的模块化机器人标定方法．首先，采用旋量的指数形式对子装配体进行数学描述，建立子装配体的运动学模型．然后，采用局部指数积方法，建立基于子装配体、包含关节约束条件的模块化机器人实际运动学模型．通过对运动学模型取微分，根据指数映射微分公式的显式表达式，给出模块化机器人末端位置误差与子装配体的关节旋量误差、末端子装配体的局部位置误差之间映射关系的显式表达．最后，以一套模块化可重构机械臂系统为试验平台，采用激光跟踪仪为测量设备进行试验．试验结果表明标定过程能够收敛到稳定值，经参数标定后用于试验的6自由度模块化机械臂定位误差模的平均值降低了近95%，最大值降低了近92%．

Abstract: A kinematic-parameter calibration method for the reconfigurable modular robot system is studied based on the local product of exponential (local POE) formula, and a calibration method for modular robot based on sub-assemblies is presented. Firstly, the sub-assemblies are described in the twist exponential form, and their kinematic model is established. Then, an actual kinematic model for modular robot based on sub-assemblies is established by using the local POE formula, which includes the joint constraint conditions. By differentiating the kinematic model and employing the explicit expression of the differential of the exponential mapping, the explicit expression of the mapping relationship between the position errors at the end of the modular robot and the errors in the joint twists of the sub-assemblies and in the local position of the terminal sub-assembly is given. Finally, a modular reconfigurable robot system is taken as the experiment platform, and some tests are carried out with the help of a laser tracker. The test result shows that the calibration process can converge to a stable value. After the parameter calibration, the mean value of the modulus of the positioning errors of the 6-DOF (degree-of-freedom) modular manipulator in the tests, is reduced by about 95% and the maximum value is reduced by about 92%.

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