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Forward Kinematics Analysis of a 3-PRR Planer Parallel Robot Using a Combined Method Based on the Neural Network

机译:基于神经网络的组合方法对3-PRR平面并联机器人的正向运动学分析

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Forward kinematics problem has always been a controversial topic in the case of parallel robots because of the close loop structure and the complicated nonlinear system of equations. In this paper, the forward kinematics problem of a planar parallel robot in its workspace is considered and a neural network based solution is proposed. In this approach, the robot's workspace is segmented into several subspaces for improving the accuracy of the solutions. Then, the pose of the parallel robot is precisely estimated using a neural network for each subspace. In order to determine the validity of this approach, the circular motion of a 3-PRR planar parallel robot is simulated by applying the proposed method. The simulation results indicate the advantages of this approach compared to other methods.
机译:由于并联回路的结构和复杂的非线性方程组,正向运动学问题一直是并联机器人中一个有争议的话题。在本文中,考虑了平面并联机器人在其工作空间中的正向运动学问题,并提出了基于神经网络的解决方案。在这种方法中,机器人的工作空间被分成几个子空间,以提高解决方案的准确性。然后,使用神经网络为每个子空间精确估计并行机器人的姿势。为了确定这种方法的有效性,通过应用该方法对3-PRR平面并联机器人的圆周运动进行了仿真。仿真结果表明,与其他方法相比,该方法具有优势。

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