不需要标定系统模型的"眼在手上"视觉伺服控制技术

工业实践中不可能精确地标定摄像机和机器人模型，但当前的视觉伺服控制都需要标定系统模型．针对这一现象，提出一种新颖的、能应用于“眼在手上”视觉伺服控制结构的动态无标定的视觉伺服控制算法，无需标定摄像机和机器人运动学模型即可跟踪运动物体，通过将非线性目标函数最小化，以视觉信息跟踪动态图像．针对目前视觉伺服控制系统中“眼在手上”系统的复合雅克比矩阵随每个时间增量的变化无法计算的现象，提出了对每一时间增量时刻的图像雅克比矩阵的变化做出估计的方法，仿真实验证明了上述方法的正确性和有效性．

Technique for uncalibrated eye-in-hand visual servoing

It is impossible to precisely calibrate cameras and robotic models in industrial practice, but most of the current visual servoing systems must calibrate their system model. Therefore, a novel dynamic uncalibrated eye-in-hand visual servoing system is proposed, which can track moving targets without needing to calibrate the camera and the kinematic model of the robot. A vision guiding algorithm for tracking dynamic images was developed by minimizing the nonlinear objective function. In current eye-in-hand visual servoing systems, it is impossible to calculate changes to the composite Jacobian matrix with every time in- crement. To solve this problem, in this paper, we propose a method to estimate this change. Simulation results demonstrated the effectiveness of the approach.