基于ROS的机器人自动手眼标定系统设计

为了缩短标定的时间,设计了一种基于ROS的机器人自动手眼标定系统。通过分析坐标系间的转换关系,建立了手眼标定的数学模型,推导了两步法的具体解法。为了尽可能减小标定误差,提出了带约束的随机增量法,并根据角点检测结果实时剔除标定过程中出现的无效图像。基于ROS软件平台完成了驱动、运动空间规划、图像处理和标定解算等功能模块的逻辑设计和系统级联。以6自由度工业机械臂UR3和RGB-D相机Kinect2构建了手眼标定实验系统,实验结果表明,与传统标定流程相比,所设计的自动手眼标定系统便捷高效且精度高,具有较强的拓展性。

Automatic Hand-Eye Calibration System of Robot based on ROS

To reduce the time of calibration,we designed a fast online hand-eye calibration system based on ROS for cameras and robots.The mathematical model of hand-eye calibration was established through analyzing the transformation among the coordinate systems.Based on the model,the two-step method was derived.To reduce the error of calibration,a method of random increment with constraint was proposed.The invalid image was discarded according to the result of corner detection in real time.Based on ROS,each module of the system was designed independently and blended into the whole system,including modules of drive,motion space planning,image processing,data processing and visualization.The experimental system was setup with a 6-degree-of-freedom,the UR3,and a RGB-D camera,the Kinect2.The results show that the automatic hand-eye calibration system is more convenient and more accurate than traditional solution,and has strong extensibility.