融合旋转平移信息的机器人手眼标定方法

针对传统手眼标定方法在四自由度机器人和六自由度机器人旋转运动约束信息不满秩时无法求解的弊端,不同于传统手眼标定方法,除了包含旋转运动约束信息,同时增加了平移运动约束信息,提出了一种融合2种运动信息的约束矩阵构造方法,详细分析了约束矩阵的秩情况,并根据不同情况构造约束矩阵保证其满秩,便于计算旋转矩阵和平移向量。在实验中,分别进行了不同运动构型的六自由度机器人(Yskawa-Motoman-MH80)手眼标定实验,用相机获取不同位置的靶标图像,实验结果表明该方法即使在旋转信息不充足的情况下依然有效。另外,四自由度桌面式机器人(Yamaha Y500)手眼标定实验结果也成功地标定出了手眼关系。

Hand eye calibration method fusing rotational and translational constraint information

Aiming at the drawback that traditional hand eye calibration method only adopts the rotational information, and can not achieve a valid solution when the rank of the constraint matrix is not full. This drawback makes the traditional method can not handle the hand eye calibration of 4 DOF and 6 DOF robots with the degraded motion configuration. In this paper, we proposes a general method of hand eye calibration, which fuses the rotational constraint information and translational constraint information to generate the expanded constraint matrix. The rank of the expanded constraint matrix is analyzed, and the corresponding methods of constructing the constraint matrix and ensuring that the matrix is full rank are provided for different situations, which facilitates the calculation of the rotational matrix and translation vector. In the experiment, a 6 DOF robot, Yskawa Motoman MH80, was controlled to move the target object to different poses and a camera was adopted to capture the images for different positions. The hand eye calibration was conducted in different motion configurations, and the results show that the proposed method is effective, even if the rotational information is not sufficient for the traditional method. Another experiment was implemented on a 4 DOF robot, Yamaha Y500. The proposed method also calibrates the relation between the robot base and the eye.