摘要
提高三维表面扫描机器人的本体定位精度是其用于制造加工质量控制的关键,提出一种基于三坐标测量机和二进制人工蜂群(Binary artificial bee colony,BABC)算法优化的机器人本体最优形位标定方法。该方法设计并加工一个测量转接件,利用三坐标测量机获得在多个机器人位姿下的转接件上精确的球心坐标,同时通过串口获得机器人的6个关节角度值。利用机器人的辨识雅可比矩阵,建立机器人运动学本体最优形位标定的目标函数,通过所提出的具有约束条件的BABC优化得到机器人运动学标定的最优形位,得到实际的机器人D-H参数。将最优形位标定获得的实际D-H参数和随机测量形位标定所得到的实际D-H参数应用于修正后的机器人运动学模型,由未参与计算的验证点数据表明,将所提出的BABC应用于机器人最优形位标定后,机器人的标定效果优于随机测量形位标定的方法。
In order to apply the three-dimensional surface scanning robot in manufacturing quality control,the robot positioning accuracy is the key element.A binary artificial bee colony（BABC） algorithm and coordinate measurement machine（CMM） approach are adopted to obtain optimal or near optimal measurement configurations for robot calibration.A measurement transition part which consists of three standard balls is designed and manufactured.The transition part is mounted to the end of the robot and then the accurate centroids of balls under many different robot measurement configurations are obtained via CMM,while the six joint angle values of the robot are acquired via serial port.The object function for optimal measurement configurations is established by using identification Jacobian matrix.After the determination of initial optimization parameters,the optimal selection of measurement configurations are obtained by proposed constrained BABC method.The real D-H parameters are determined.The obtained real parameters are employed in the modified kinematic model and experimental results demonstrate that its calibration performance is better than that of the random selection measurement configurations.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2013年第17期130-136,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金(51249006)
集美大学李尚大学科建设基金(ZC2012010)
集美大学科研基金(Z81104)资助项目
关键词
机器人
最优形位
三坐标测量机
人工蜂群算法
Robot Optimal measurement configuration Coordinate measurement machine Artificial bee colony algorithm
