BETTERING OPERATION OF ROBOTS BY LEARNING
BETTERING OPERATION OF ROBOTS BY LEARNING
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DOI：
10.1002/rob.4620010203
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发表时间：
1984-01-01
期刊：
影响因子：
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通讯作者：
MIYAZAKI, F
中科院分区：
文献类型：
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作者：
ARIMOTO, S;KAWAMURA, S;MIYAZAKI, F
本文提出了一种机械机器人操作的改进过程，从某种意义上说，它通过使用先前操作的数据来改进机器人的下一次操作。该过程具有迭代学习结构，使得关节致动器的第（k+1）个输入由第k个输入加上由第k个运动轨迹与给定的期望运动轨迹之间的导数差组成的误差增量组成。在一些合理的条件下，可以确保该过程收敛到所需的运动轨迹。计算机模拟的数值结果显示了所提出的学习方案的有效性。
This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous operation's data. The process has an iterative learning structure such that the (k+ 1)th input to joint actuators consists of thekth input plus an error increment composed of the derivative difference between thekth motion trajectory and the given desired motion trajectory. The convergence of the process to the desired motion trajectory is assured under some reasonable conditions. Numerical results by computer simulation are presented to show the effectiveness of the proposed learning scheme.