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Kinematics Modeling and Real-Time Seam Tracking for Welding Mobile Robot

机译:焊接移动机器人的运动学建模和实时焊缝跟踪

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Kinematics modeLing of the developed welding mobile robot is presented and a real time seam tracking algorithm based on fuzzy neural network is proposed. At first, the kinematics behavior of mobile robot body and cross sLiders action to the welding torch are investigated by the Denavit-Hartenberg(D-H) Homogeneous transformation method, and a full kinematics model is estabLished. And then a seam tracking controller based on fuzzy-gaussian neural network (FGNN) is described by applying a Gaussian function as an activation function, lateral sLider position and heading angle of the robot act as input signals, and adjusted angle for welding torch acts as output, a speciaLized learning architecture is used so that membership function can be tuned in real time by applying the back propagation algorithm of FGNN controller. The experiment results show that the proposed controller has excellent tracing accuracy (within ±0.5mm), and can satisfy the requirement of practical welding project.
机译:给出了已开发的焊接移动机器人的运动学模型,提出了一种基于模糊神经网络的实时焊缝跟踪算法。首先,利用Denavit-Hartenberg(D-H)同质变换方法研究了移动机器人的机体运动和十字滑动器对焊炬的运动,建立了完整的运动学模型。然后通过应用高斯函数作为激活函数,以机器人的侧向滑行位置和航向角作为输入信号,并以调整后的焊枪角度作为输入信号,描述了基于模糊高斯神经网络(FGNN)的焊缝跟踪控制器。输出时,使用特定的学习体系结构,以便通过应用FGNN控制器的反向传播算法可以实时调整隶属函数。实验结果表明,所提出的控制器具有良好的跟踪精度(±0.5mm以内),可以满足实际焊接工程的要求。

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