Basic Research on Visual Servo System which Dynamically Combines the Position/Force Control and Environment Recognition

位置/力控制与环境识别动态结合的视觉伺服系统基础研究

基本信息

批准号：
04452157
负责人：
KIMURA Hidenori
金额：
$ 4.54万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1992
资助国家：
日本
起止时间：
1992 至 1994
项目状态：
已结题

项目摘要

Previous visual feedback control schemes assumed ideal tracking performance of the joint servo mechanisms.The robot dynamics wereneglected when designing the visual servo systems. Thus they were notsuitable for high speed motions. The investigators developed a newvisual servoing scheme which considers the visual servo system as a dynamical system and which computes the inverse dynamics of the visual servo system in the task level.However, the task level inverse dynamic scheme does not have the model of the object motion. Thus it only guarantees the convergence for the step motion of the object, in other words it is the type 1 servo system. Therefore errors are inevitable if the object moves continuously. The investigators formulated the conditions required to track the continuous object motions and proposed a tracking controller which adaptively estimates the object motions.The proposed control scheme is composed of two modules, one is a nonlinear observer which estimates the object motion and the other is the task level inverse dynamics based on the estimated object velocity. The investigators proved the asymptotic stability of the proposed method. The effectiveness of the proposed method is validated by the real time experiments on the 2 link direct drive robot. Moreover, a position/force controller was implemented on the 2 link DD robot and ball-on-ball control was performed. The ball-on ball controlis similar to the inverted pendulum. A small ball is controlled tokeep the top of the other larger ball which is attached to the end ofthe 2 link robot. The camera is used to obtain the small ball position which compensate the noisy output of the force sensor. The visual information is proven to be effective to stabilize the ball. At present the combination of the force control and the environment recognition is not satisfactory, but the nonlinear observer developed in this research project will play a important role in the future study.

先前的视觉反馈控制方案假定了关节伺服机制的理想跟踪性能。在设计视觉伺服系统时，机器人动力学会逐渐绘制。因此，它们不适合高速运动。研究人员开发了一种新的宣传方案，该方案将视觉伺服系统视为动力系统，并在任务级别计算Visual Servo系统的逆动力学。但是，任务级别的反向动态方案没有对象运动的模型。因此，它仅保证对象的步骤运动的收敛性，换句话说是类型1伺服系统。因此，如果对象连续移动，则不可避免地会出现错误。研究人员制定了跟踪连续对象运动所需的条件，并提出了一个跟踪控制器，该跟踪控制器可适应对象动作。拟议的控制方案由两个模块组成，一个是一个非线性观察者，它估计对象运动，另一个是基于估计的对象速度的任务级别的逆动力学。研究人员证明了该方法的渐近稳定性。提出方法的有效性通过2个链接直接驱动机器人的实时实验验证。此外，在2个链接DD机器人上实现了位置/力控制器，并执行了球球对照。球形控制的球与倒摆的相似之处。一个小球由附着在2个链接机器人末端的另一个较大球的顶部控制。该相机用于获得小球位置，以补偿力传感器的嘈杂输出。事实证明，视觉信息可有效稳定球。目前，力控制和环境识别的结合并不令人满意，但是该研究项目中开发的非线性观察者将在未来的研究中发挥重要作用。