摘要
在无标定视觉伺服控制中,高斯牛顿法是一种被广泛采用的方法,但在大残量情况时,该方法可能不收敛或不能收敛到期望值。对此,提出了一种采用L-M方法的无标定视觉伺服控制方法。该方法采用信赖域策略确保模型是对非线性目标函数合适的模拟,并根据函数实际下降量与预测下降量的比值自适应地改变步长,采用Broyden方法动态估计图像雅可比矩阵。采用该方法无需对机器人及摄像机进行标定,且避免了传统方法的上述缺点。仿真及实验结果验证了该方法的有效性。
Gauss-Newton method is most commonly used in uncalibrated visual servo control, but it may not be convergent or unable to converge to the expected value in large residual cases. So, a new uncalibrated visual servo control method using Levenberg-Marquardt method was proposed. The trust region strategy was used to insure that the model was a good simulation of the nonlinear function and the step was adjusted adaptively by the ratio between actual decrease of the function and the predicted decrease in this method. Besides, the Broyden＇s method was used to estimate the image Jacobian online. The disadvantages of traditional method are avoided and it does not need to calibrate the camera and the robot by using this method. Simulation and experimental results demonstrate the success of the method.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2008年第21期2622-2626,共5页
China Mechanical Engineering
基金
国家自然科学基金资助项目(70272046)
