Learning a coordinate transformation for a human visual feedback controller based on disturbance noise and the feedback error signal
Learning a coordinate transformation for a human visual feedback controller based on disturbance noise and the feedback error signal
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基于干扰噪声和反馈误差信号学习人类视觉反馈控制器的坐标变换
DOI：
10.1109/robot.2001.933272
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
K. Macdorman
中科院分区：
文献类型：
--
作者：
E. Oyama;N. Chong;A. Agah;K. Macdorman
人类运动的速度、准确性和适应性取决于大脑根据经验学习执行逆运动学变换，即从视觉坐标到关节角坐标的变换。在人体运动控制中，学习人体逆运动学求解器中手部位置误差的反馈控制器非常重要。本文提出了一种新模型，使用干扰噪声和反馈误差信号来学习人类视觉反馈控制器的坐标变换。所提出的模型纠正了当前模型的缺点，因为它不依赖于复杂的信号切换，这在神经生理学上似乎不合理。数值模拟显示了模型的有效性。
The speed, accuracy, and adaptability of human movement depends on the brain performing an inverse kinematics transformation-that is, a transformation from visual to joint angle coordinates-based on learning from experience. In human motion control, it is important to learn a feedback controller for the hand position error in the human inverse kinematics solver. This paper proposes a novel model that uses disturbance noise and the feedback error signal to learn coordinate transformations of the human visual feedback controller. The proposed model redresses drawbacks in current models because it does not rely on complex signal switching, which does not seem neurophysiologically plausible. Numerical simulations show the effectiveness of the model.