基于状态空间的视觉伺服系统参数估计方法研究及应用

项目名称： 基于状态空间的视觉伺服系统参数估计方法研究及应用

项目编号： No.61503224

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 王海霞

作者单位： 山东科技大学

项目金额： 22万元

中文摘要： 雅可比矩阵的参数估计精度是决定视觉伺服系统控制精度的一个关键因素。目前很多估计方法为避免对摄像机标定的依赖，采用在线迭代估计方法，但它们受初值和传感器时延影响较大，而且随着机器人关节数量增多，计算量增大、估计精度降低。本项目以手眼式双目6自由度串联机器人为研究对象，拟探索一种新的雅可比矩阵参数估计方法。首先建立整体系统标定模型，并同时考虑双目摄像机引起的时延效应，建立含当前观测和时延观测状态空间模型；其次，利用一种简单灵活的SAI整体标定方法实现摄像机和机器人本体同时标定，得到雅可比矩阵初值；然后，对双观测模型，基于观测重组方法给出最优估计器，并进一步针对部分噪声统计特性未知的情况给出雅可比矩阵鲁棒估计方法；最后将上述结果应用在视觉伺服系统中。本研究在保证控制精度的前提下可望减小对系统标定误差的依赖性，有效提高系统的鲁棒性，进而可以初步建立新型雅可比矩阵估计理论，具有重要的理论和实际意义。

中文关键词： Kalman滤波；雅可比矩阵估计；观测重组方法；视觉伺服；时延

英文摘要： The estimation precision of parameters in Jacobian matrix is a key factor on the control precision of visual servoing system. Currently many estimation methods adopt the on-line recursive scheme to reduce the effects due to the possible inaccuracy in the camera calibration. However, the estimation precision of those methods is greatly affected by the selected initial values of parameters and the delays caused by sensors. Besides with the increase of the number of robot joints, the computation burden will increase and the estimation precision will decrease. In this project, a 6-freedom-serial robot with a hand-eye binocular vision is taken as the research platform, and we aim to present a new method for Jacobian matrix estimation. Firstly, the whole system calibration model and the parameter estimation model are built in terms of state space which contains instantaneous and delayed observations caused by two visual sensors. Secondly, a simple and flexible robot whole calibration method based on SAI is presented to calibrate the camera and the robot at the same time to obtain an initialization for Jacobian matrix. Thirdly, the model with two observations is optimized using a measurement-reorganization method. Furthermore, a robust estimator is also given for the delayed system model when the statistic characteristics of noises are unknown. Finally, the above results will be verified and used in the visual servoing system. This project is expected to provide a new Jacobian matrix estimation theory which could decrease the dependence on the calibration error, and increase the robustness of the system, and is of theoretical and practical significance.

英文关键词： Kalman filtering;Jacobian matrix estimation;measurement-reorganization meyhod;visual servoing;delay