摘要
在视觉伺服控制过程中无法精确地标定摄像机和机器人运动学模型,而当前的无标定视觉伺服控制技术或者只能针对静态的目标,或者针对动态目标但无法摆脱大偏差的影响.针对此问题,提出一种动态无标定的视觉伺服控制方法:基于非线性方差最小化法控制机器人跟踪运动目标,利用动态拟牛顿法估计图像雅克比矩阵,采用迭代最小二乘法提高系统的稳定性并提出大偏差条件下的无标定控制策略.仿真实验证明了该方法的正确性和有效性.
It is impossible to get precise parameters to calibrate model of camera and robot kinematics, while some uncalibrated visual servoing technique are only for static target and some for dynamic target but can not dismiss effect of large residual. An uncalibrated method for visual servoing lechnique is presented. The robot system is controlled using dynamic nonlinear least squares optimization technique to tracking moving target. Dynamic quasi- Newton approach is used to estimate image-jacobian matrix. System is more stable using recursive least squares algorithm. The approach for estimation of large residual is proposed. Simulation result shows that the algorithm is of validate and correct.
出处
《控制与决策》
EI
CSCD
北大核心
2006年第9期1015-1019,共5页
Control and Decision
基金
国家863计划项目(2001AA422250)
