网络四旋翼机中感知-预测-驱动TDMA延迟降低方案

Anandarup Mukherjee, S. Misra, N. Raghuwanshi
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引用次数: 0

摘要

在本文中,我们提出使用基于长短期记忆(LSTM)的服务器端序列预测算法来缓解空中机器人平台上多个传感器的快速轮询所造成的网络数据负载,这些传感器通过无线连接到远程服务器进行控制和协调。我们的方案减少了这些平台和远程服务器托管控制和调度机制之间的网络访问时间延迟。减少基于tdma的访问时间是通过减少在网络上传输的实际数据量来实现的,使用在网络上部分传输实际传感器数据和服务器端序列预测自愿错过的传感器值。我们的方案允许TDMA控制越来越多的网络平台,而不改变基础设施或网络特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPA: A sense-predict-actuate TDMA latency reduction scheme in networked quadrotors
In this paper, we propose the use of a Long Short-Term Memory (LSTM) based server-side sequence prediction algorithm to ease network data-load caused by rapid polling of multiple sensors onboard aerial robotic platforms, which are wirelessly tethered to a remote server for control and coordination. Our scheme reduces the network access time latencies between these platforms and the remote server hosting the control and scheduling mechanisms. Reduction in the TDMA-based access time is achieved by reducing the actual amount of data transmitted over the network, using partial transmission of actual sensor data over the network and server-side sequence prediction of the voluntarily missed sensor values. Our scheme allows the TDMA control of an increased number of networked platforms without change of infrastructure or the network characteristics.
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