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Temporal difference approach to coordinated motion control of cooperating two link robots

机译:协调两个链路机器人协调运动控制的时间差异方法

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To perform complex manufacturing operations, two or more manipulators are made to work in concert. When robots work independently of other robots, small errors made (e.g., due to inaccuracies in modeling of the manipulator) by individual robots may be acceptable. However, when robots work together, then high precision is required. This calls for the use of adaptive controllers in order to minimize errors. This paper discusses the application of Temporal Difference Learning (TDL) method, wherein stiffness of manipulator is adapted based on the feedback obtained from force/torque sensors. In order to accomplish this, simulation was carried out by adding feedback (force and change of force) to controllers, so that required trajectory could be adhered. Normally this error (deviation from required trajectory) occurs due to non-availability of the correct values of stiffness of the system. Stiffness of system is difficult to calculate due to inherent complexities in formulating an accurate dynamic model of system. Variation in parameters, for example change of friction due to aging, change of moment of inertia due to changes in payload position and orientation, significantly affect the dynamic model of manipulator. One of the ways to achieve compliance is by updating the dynamic model of the system. The other way is to use the external control loop which provide manipulator with set-points such that the desired compliance can be achieved [1]. This paper demonstrates the appropriateness of TDL method in updating the dynamic model of the system. This updated model is then used to calculate the torques of the joints. As the process of learning converges, the function learned represents a nearly perfect model of the stiffness of the system.
机译:为了执行复杂的制造操作,将两种或更多种操作器与音乐会一起工作。当机器人独立于其他机器人工作时,各个机器人可以接受小错误(例如,由于操纵器的建模中的不准确)。但是,当机器人一起工作时,需要高精度。这需要使用自适应控制器以最小化错误。本文讨论了时间差学习(TDL)方法的应用,其中机械手的刚度基于从力/扭矩传感器获得的反馈来调整。为了实现这一点,通过将反馈(力和力的变化)添加到控制器来执行模拟,从而可以遵循所需的轨迹。通常,由于系统的刚度值的正确值,发生这种错误(从所需轨迹的偏差)发生。由于制定了精确动态系统的固有复杂性,系统的刚度难以计算。参数的变化,例如由于老化引起的摩擦的变化,由于有效载荷位置和方向的变化而导致的惯性矩变化,显着影响了操纵器的动态模型。实现合规性之一是通过更新系统的动态模型。另一种方法是使用外部控制回路,该环路提供具有设定点的机械手,使得可以实现所需的顺应性[1]。本文展示了TDL方法在更新系统动态模型时的适当性。然后使用该更新的模型来计算关节的扭矩。作为学习融合的过程,学习的功能代表了系统刚度的几乎完美的模型。

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