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Application of ANN in Identification of Inertial Parameters of End-Effector of Robot

机译:人工神经网络在机器人末端执行器惯性参数辨识中的应用

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Identification of inertial parameters of manipulator of a robot is an important basic problem in robot dynamical research. Algorithm and mathematical model of inertial parameters identification of robot are analyzed in this paper. General rules and advantages of application of artificial neural network in identification of parameters of system are investigated also. A novel method different from the traditional ANN problems is developed. The structure and the weights of the network constructed have special physical meanings in this method. Difficulty in obtaining the training samples, which exists in the traditional ANN for inertial parameters estimation, is resolved. This method is simple, direct and less in operand, which can be applied on the end-effector of a robot on line to estimate its inertial parameters based on the signal of sensors. Feasibility and effectiveness of this method are proved by the results of experiment carried out in a PUMA562 robot.
机译:机器人操纵器惯性参数的辨识是机器人动力学研究的重要基础问题。分析了机器人惯性参数辨识的算法和数学模型。研究了人工神经网络在系统参数辨识中的一般规律和优势。提出了一种不同于传统人工神经网络问题的新方法。这种方法构造的网络的结构和权重具有特殊的物理意义。解决了传统人工神经网络中惯性参数估计中存在的训练样本获取困难的问题。该方法简单,直接,操作数少,可应用于在线机器人的末端执行器,根据传感器信号估计其惯性参数。在PUMA562机器人上进行的实验结果证明了该方法的可行性和有效性。

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