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用于柔性模块化机器人步态频率同步的尖峰神经网络状态机。

Spiking neural state machine for gait frequency entrainment in a flexible modular robot.

机构信息

Department of Electrical and Computer Engineering, University of California, Santa Cruz, Santa Cruz, California, United States of America.

Genomics Institute, University of California, Santa Cruz, Santa Cruz, California, United States of America.

出版信息

PLoS One. 2020 Oct 21;15(10):e0240267. doi: 10.1371/journal.pone.0240267. eCollection 2020.

Abstract

We propose a modular architecture for neuromorphic closed-loop control based on bistable relaxation oscillator modules consisting of three spiking neurons each. Like its biological prototypes, this basic component is robust to parameter variation but can be modulated by external inputs. By combining these modules, we can construct a neural state machine capable of generating the cyclic or repetitive behaviors necessary for legged locomotion. A concrete case study for the approach is provided by a modular robot constructed from flexible plastic volumetric pixels, in which we produce a forward crawling gait entrained to the natural frequency of the robot by a minimal system of twelve neurons organized into four modules.

摘要

我们提出了一种基于双稳态弛豫振荡器模块的神经形态闭环控制的模块化架构,每个模块由三个尖峰神经元组成。与生物原型一样,这个基本组件对参数变化具有鲁棒性,但可以通过外部输入进行调制。通过组合这些模块,我们可以构建一个能够产生腿部运动所需的循环或重复行为的神经状态机。一个具体的案例研究是由柔性塑料体素像素构成的模块化机器人,我们通过一个由四个模块组成的十二神经元最小系统,产生了一个与机器人自然频率同步的前进爬行步态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6465/7577446/77f509a51ecd/pone.0240267.g003.jpg

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