Nicola Russo, Haochun Huang, E. Donati, Thomas Madsen, K. Nikolic
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引用次数: 3
摘要
神经形态计算有望成为低功耗人工智能应用的未来标准。新的神经形态硬件和传统微控制器之间的集成是一个开放的挑战。在本文中,我们提出了一个接口板和一个通信协议,允许不同设备之间的通信,中间使用微控制器单元(Arduino Due)。我们的紧凑型印刷电路板(PCB)将不同的设备连接成一个整体系统,并使用电池作为电源为整个系统提供电源。具体而言,我们将动态视觉传感器(DVS128), SpiNNaker板和伺服电机连接在一起,创建了一个由spike神经网络控制的神经形态机器人系统平台,并在拦截传入物体的任务中进行了演示。实现的接口板的数据速率为24.64 k symbols/s,生成命令的延迟约为11ms。整个系统仅由电池驱动,因此非常适合机器人应用。
An Interface Platform for Robotic Neuromorphic Systems
Neuromorphic computing is promising to become a future standard in low-power AI applications. The integration between new neuromorphic hardware and traditional microcontrollers is an open challenge. In this paper, we present an interface board and a communication protocol that allows communication between different devices, using a microcontroller unit (Arduino Due) in the middle. Our compact printed circuit board (PCB) links different devices as a whole system and provides a power supply for the entire system using batteries as the power supply. Concretely, we have connected a Dynamic Vision Sensor (DVS128), SpiNNaker board and a servo motor, creating a platform for a neuromorphic robotic system controlled by a Spiking Neural Network, which is demonstrated on the task of intercepting incoming objects. The data rate of the implemented interface board is 24.64 k symbols/s and the latency for generating commands is about 11ms. The complete system is run only by batteries, making it very suitable for robotic applications.