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首页> 外文会议>IACSIT/IACT/UASTRO International Conference on Aerospace, Robotics,anufacturing Systems, Mechanical Engineering, Biomechatornics and Neurorehabilitation >Optimization of the Robot's Position Base Point by Using the Proper Algorithm and Iterative Pseudo Inverse Jacobian Neural Network Matrix Method
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Optimization of the Robot's Position Base Point by Using the Proper Algorithm and Iterative Pseudo Inverse Jacobian Neural Network Matrix Method

机译：通过使用适当的算法和迭代伪逆雅代族神经网络矩阵方法优化机器人位置基点的位置基点

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摘要

In the robotized production one of the more important think is to choose the optimal solution to use the robots with respect an objective function which represents, for example, minimum time of motion during a application, or minimum consumption of energy, or maximum precision, or combination of these. Some objective functions could results from the specificity of the application like is the case of casting of forging, where the minimum of the accumulation of heat could be one of the optimization criteria. In the controlling of the space movement of the end effecter and the robot's joints of the all robots from the applications, one of the most important think is to know, with the extreme precision, the joints relative displacements of all robots. One of the most precise method to solve the inverse kinematics problem in the robots with redundant chain is the complex coupled method of the neural network with Iterative Pseudo Inverse Jacobian Matrix Method. In this paper was used the proper coupled method Iterative Pseudo Inverse Jacobian Matrix Method (IPIJMM) with Sigmoid Bipolar Hyperbolic Tangent Neural Network with Time Delay and Recurrent Links (SBHTNN-TDRL) to establish the optimal position of the application point of the robot's base with respect simultaneously two objective functions: the extreme precision and the minimum of the movements time. The presented method and the virtual instrumentations (VI) are generally and they can be used in all other robots application and for all other conventional and unconventional space curves.
机译：在更重要想到的机器人化生产一个是选择最佳的解决方案中使用的机器人相对于目标函数表示，例如，运动的最小时间一个应用过程中，或能量的最小消耗，或最大精度，或它们的组合。一些客观的功能可以从应用程序的特殊性结果就像是锻造，其中的热量积累的最小可能的优化标准之一的铸造的情况。在末端执行器，并从应用程序的所有机器人的机器人的关节空间运动的控制，最重要的思考之一是要知道，用极高的精度，所有机器人的相对关节位移。一个解决与冗余链机器人逆运动学问题的最精确的方法是用迭代伪逆雅可比矩阵法的神经网络的复杂耦合方法。在本文中使用具有乙状结肠双极双曲正切神经网络的适当的耦合方法的迭代伪逆雅可比矩阵法（IPIJMM）具有时滞和复发性链接（SBHTNN-TDRL）建立机器人的基部的与所述应用点的最佳位置同时尊重两个目标函数：极端精度及最小的运动时间。所提出的方法和虚拟控制仪表（VI）通常是，它们可以在所有其他机器人的应用和对所有其他常规和非常规的空间曲线来使用。

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