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首页> 外文会议>International Conference on Manufacturing Science and Technology >Increase the Space Trajectory Precision by Using the Proper Assisted Research Method for Inverse Kinematics Problem
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Increase the Space Trajectory Precision by Using the Proper Assisted Research Method for Inverse Kinematics Problem

机译：通过使用逆运动学问题的适当辅助研究方法提高空间轨迹精度

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摘要

Inverse kinematics model of the industrial robot is used in the control of the end-effecter trajectory. The solution of the inverse kinematics problem is very difficult to find, when the degree of freedom increase and in many cases this is impossible. In these cases is used the numerical approximation or other method with diffuse logic. The paper showed one new method for optimization of the inverse cinematic solution by applying the proper assisted Iterative Pseudo Inverse Jacobian Matrix Method coupled with proper Sigmoid Bipolar Hyperbolic Tangent Neural Network with Time Delay and Recurrent Links Method (IPIJMM-SBHTNN-TDRLM). In the paper was shown one case study to obtain one space circle curve by using one arm type robot and the proposed method. The errors of the space coordinates of the circle, after applying the proposed method, was less than 0.001. The study has contained the determining the internal coordinates corresponding to the external coordinates of the circle space curve, by solving the inverse kinematics with the proposed method and after that, by applying the forward kinematics to this coordinates, were obtained the external coordinates, what were compared with the theoretical one. The presented method is general and it can be used in all other robots types and for all other conventional and unconventional space curves.
机译：工业机器人的反向运动学模型用于控制最终效应轨迹。逆运动学问题的解决方案很难找到，当自由度增加和许多情况下，这是不可能的。在这些情况下，使用漫射逻辑的数值近似或其他方法。本文通过应用了具有时间延迟和复发链路方法（ipijmm-sbhtnn-tdrlm）的适当辅助迭代伪偏心族族矩阵方法，通过应用适当的辅助迭代伪曲线血管矩阵方法来优化逆电影解决方案的一种新方法（ipijmm-sbhtnn-tdrlm）。在本文中，示出了一种案例研究，通过使用一种臂式机器人和所提出的方法来获得一个空间圆曲线。在施加所提出的方法后，圆的空间坐标的误差小于0.001。该研究包含了通过用所提出的方法求解逆运动学，然后通过将前进运动学应用于这种坐标来获得外部坐标，以后，获得了外部坐标，以后的外部坐标与理论相比。呈现的方法是一般的，它可以用于所有其他机器人类型和所有其他传统和非传统空间曲线。

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