Generating Image Trajectories and Direct Image Jacobians for Visual Servoing

生成用于视觉伺服的图像轨迹和直接图像雅克比行列式

• 批准号: 0097717
• 负责人: Nicola Ferrier
• 金额: $ 17.16万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-06-15 至 2005-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0097717&HistoricalAwards=false
• 关键词: Generating; Image; Trajectories; Direct; Jacobians

This is a three year standard award. Visual servoing, the use of visual feedback in the control of a robot end-effector, can provide a superior robot interface than those offered by teach pendants or tele-operated systems. Visual servoing is advantageous when precise fixturing is impractical or impossible. In image based servoing, control is effected in the image. This method has the advantages that one does not have to reconstruct 3D information about the robot's environment, and that control laws exist that are not overly sensitive to camera calibration errors. However, there are problems with image based servoing that need to be overcome in order to develop robust, stable systems. This project will address two issues impeding the application of image-based servoing. First, image feature-point path planning methods will be developed and demonstrated. Previous research efforts have focused on the form, and possible decompositions, of the "Image Jacobian", relating manipulator velocities to image motion. In contrast, this project will develop methods to determining a path within the image to use as input to a "standard" image-based regulator. The PI's approach will both improve controller performance and also ensure the image features remain within the field of view during the manipulation task. Second, a parameterized direct image-to-actuator model will be analyzed, evaluated, tested, and compared with classical approaches. The error signal from the image together with the image Jacobian typically map to end-effector velocities which then must be converted to actuator velocities using the robot kinematic model. A controller that converts image displacements directly to actuator commands would eliminate the intermediate step thus enhancing system performance, both in terms of speed and accuracy. Addressing issues of robustness and sensitivity will facilitate application of these techniques outside of the laboratory. Success of this project will facilitate the acceptance of image based servo techniques as a viable control method in production operations. The key scientific contributions created by this effort will include advances in the design of image based visual servo controllers through (1) the introduction of superior robot motion command generation created through image path planning and (2) the introduction of a parameterized direct image Jacobian with appropriate understanding of the model's limitations.

这是一个为期三年的标准奖项。视觉伺服，在机器人末端执行器的控制中使用视觉反馈，可以提供比示教器或遥控系统提供的机器人接口更上级的机器人接口。 视觉伺服是有利的，当精确的夹具是不切实际或不可能的。在基于图像的伺服中，控制在图像中实现。 这种方法的优点是，一个不需要重建的3D信息的机器人的环境，并且存在的控制律是不过分敏感的摄像机校准误差。 然而，存在需要克服的基于图像的伺服问题，以开发鲁棒、稳定的系统。 本计画将探讨两个阻碍影像伺服应用的问题。 首先，图像特征点的路径规划方法将被开发和演示。 以前的研究工作都集中在形式上，和可能的分解，“图像雅可比矩阵”，有关机械手速度的图像运动。 相比之下，本项目将开发确定图像内路径的方法，以用作“标准”基于图像的调节器的输入。PI的方法将提高控制器性能，并确保图像特征在操纵任务期间保持在视场内。 其次，将分析、评估、测试参数化的直接图像到致动器模型，并与经典方法进行比较。 来自图像的误差信号与图像雅可比矩阵一起通常映射到末端执行器速度，然后必须使用机器人运动学模型将末端执行器速度转换为致动器速度。 将图像位移直接转换为致动器命令的控制器将消除中间步骤，从而在速度和精度方面提高系统性能。 解决鲁棒性和灵敏度问题将促进这些技术在实验室之外的应用。 这个项目的成功将促进接受图像为基础的伺服技术作为一个可行的控制方法在生产操作。 这项工作所创造的关键科学贡献将包括在基于图像的视觉伺服控制器的设计方面的进展，通过（1）引入通过图像路径规划创建的上级机器人运动命令生成，以及（2）引入参数化直接图像雅可比矩阵，并适当理解模型的局限性。