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Movement Generation and Control with Generic Neural Microcircuits

机译:通用神经微电路的运动产生和控制

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摘要

Simple linear readouts from generic neural microcircuit models can be trained to generate and control basic movements, e.g., reaching with an arm to various target points. After suitable training of these readouts on a small number of target points; reaching movements to nearby points can also be generated. Sensory or proprioceptive feedback turns out to improve the performance of the neural microcircuit model, if it arrives with a significant delay of 25 to 100 ms. Furthermore, additional feedbacks of "prediction of sensory variables" are shown to improve the performance significantly. Existing control methods in robotics that take the particular dynamics of sensors and actuators into account ("embodiment of robot control") are taken one step further with this approach which provides methods for also using the "embodiment of computation", i.e. the inherent dynamics and spatial structure of neural circuits, for the design of robot movement controllers.
机译:可以训练来自通用神经微电路模型的简单线性读数以生成和控制基本运动,例如用手臂到达各个目标点。在少数目标点上对这些读数进行适当的训练之后;也可以生成到达附近点的移动。感觉或本体感觉反馈可以改善神经微电路模型的性能,如果它以25到100 ms的明显延迟到达的话。此外,显示了“感官变量预测”的其他反馈可显着改善性能。考虑到传感器和执行器的特定动力学特性的现有机器人控制方法(“机器人控制的体现”)采用这种方法又向前迈进了一步,该方法还提供了使用“计算体现”的方法,即固有动力学和神经回路的空间结构,用于设计机器人运动控制器。

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