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.

以前的视觉反馈控制方案假设关节伺服机构具有理想的跟踪性能。在设计视觉伺服系统时忽略了机器人动力学。因此它们不适合高速运动。研究人员开发了一种新的视觉伺服方案，该方案将视觉伺服系统视为一个动力系统，并在任务级计算视觉伺服系统的逆动力学。然而，任务级逆动态方案没有物体运动的模型。因此它只保证物体步进运动的收敛，即1型伺服系统。因此，如果物体连续运动，误差是不可避免的。研究人员制定了跟踪连续物体运动所需的条件，并提出了一种自适应估计物体运动的跟踪控制器。所提出的控制方案由两个模块组成，一个是估计物体运动的非线性观测器，另一个是任务基于估计的物体速度的水平逆动力学。研究人员证明了该方法的渐近稳定性。通过在二连杆直驱机器人上的实时实验验证了该方法的有效性。此外，在 2 连杆 DD 机器人上实现了位置/力控制器，并执行了球对球控制。上球控制类似于倒立摆。控制一个小球以保持连接到 2 连杆机器人末端的另一个大球的顶部。相机用于获取小球位置，以补偿力传感器的噪声输出。事实证明，视觉信息对于稳定球是有效的。目前力控制与环境识别的结合还不够令人满意，但本研究项目开发的非线性观测器将在未来的研究中发挥重要作用。