一种机器人逆运动学求解的神经网络方法
A Neural Network Approach for Inverse Kinematics Solving of Robots
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摘要: 研究了机械手控制的逆运动学问题,提出了一种克服Hopfield网络的局部极值问题的网络参数扰动算法,通过数字模拟分析了该算法的性能,并将该算法成功地应用于机械手控制的逆运动学问题。计算机仿真表明,这种神经网络控制方法不仅具有较快的速度,而且大大提高了对机械手的控制精度。Abstract: This paper deals with manipulator inverse kinematics.A parameter disturbing algorithm of neural networks which can overcome the local minima porblem of Hopfield network is proposed.Its performance is analyzed in terms of digital simulations in detail.The algorithm is successfully applied to the inverse kinematics problem of manipulator control.It is shown by simulations that the proposed neural network controlling method not only has fast control speed but also raise the control accuracy of manipulator.