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Calibration-Free Robot-Sensor Calibration approach based on Second-Order Cone Programming

机译:基于二阶锥编程的免校准机器人传感器校准方法

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In order to overcome the restrictions of traditional robot-sensor calibration method which solve the tool-camera transformation and robot-world transformation rely on calibration target, a calibration-free approach that solve the robot-sensor calibration problem of the form AX = YB based on Second-Order Cone Programming is proposed. First, a Structure-From-Motion approach was used to recover the camera motion matrix up to scaling. Then rotation and translation matrix in calibration equation were parameterized by dual quaternion theory. Finally, the Second-Order Cone Programming method was used to simultaneously solve the optimal solution of camera motion matrix scale factor, the robot-world and hand-eye relation. The experimental results indicate that the calibration precision of rotation relative error is 3.998% and the translation relative error is 0.117% in defect of calibration target as 3D benchmark. Compared with similar methods, the proposed method can effectively improve the calibration accuracy of the robot-world and hand-eye relation, and extend the application field of robot-sensor calibration method.
机译:为了克服传统的机器人传感器校准方法的局限性,即解决工具-相机变换和机器人世界变换依赖于校准目标的问题,一种基于AX = YB形式的解决机器人传感器校准问题的免校准方法提出了关于二阶锥规划的方法。首先,采用“从结构开始运动”方法来恢复相机运动矩阵直至缩放。然后用双四元数理论对校准方程中的旋转和平移矩阵进行参数化。最后,采用二阶锥规划方法同时求解摄像机运动矩阵比例因子,机器人世界和手眼关系的最优解。实验结果表明,作为3D基准的标定目标缺陷,旋转相对误差的标定精度为3.998%,平移相对误差为0.117%。与同类方法相比,该方法可以有效提高机器人世界和手眼关系的校准精度,并扩展了机器人传感器校准方法的应用领域。

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