Open-Loop Neuromorphic Controller Implemented on VLSI Devices

Elisa Donati, Fernando Perez-Pefia, C. Bartolozzi, G. Indiveri, E. Chicca
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引用次数: 12

Abstract

An ever increasing amount of robotic platforms are being equipped with a new generation of neuromorphic computing architectures. Neuromorphic computing systems represent a promising brain-inspired technology that use asynchronous pulses to encode, transmit, and process sensory signals, typically implemented in compact low-latency and low-power devices. However, although multiple examples of sensing and processing neuromorphic devices have been successfully deployed on robotic platforms, no example of event-based neuromorphic motor controller has been proposed yet. In this paper, we present an open-loop neuromorphic controller implemented using a full-custom spiking neural network VLSI chip interfaced to motors for performing position control. The proposed controller is based on biologically inspired principles by which the discharge of motor-neuron populations produces muscle contractions. Following these principles, we use the spikes of the silicon neurons present in the neuromorphic chip to encode the target position and drive the motors using Pulse Frequency Modulation (PFM) technique, rather than the more traditional Pulse Width Modulation (PWM) one.
VLSI器件上的开环神经形态控制器
越来越多的机器人平台正在配备新一代的神经形态计算架构。神经形态计算系统代表了一种很有前途的受大脑启发的技术,它使用异步脉冲来编码、传输和处理感官信号,通常在紧凑的低延迟和低功耗设备中实现。然而,尽管传感和处理神经形态装置的多个例子已经成功地部署在机器人平台上,但尚未提出基于事件的神经形态运动控制器的例子。在本文中,我们提出了一种开环神经形态控制器,该控制器使用全定制尖峰神经网络VLSI芯片与电机接口来执行位置控制。所提出的控制器基于生物学原理,即运动神经元群的放电产生肌肉收缩。遵循这些原则,我们使用神经形态芯片中存在的硅神经元的尖峰来编码目标位置,并使用脉冲频率调制(PFM)技术驱动电机,而不是更传统的脉冲宽度调制(PWM)技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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