Towards real-time multi-sensor information retrieval in Cloud Robotic System

Lujia Wang, Ming Liu, M. Meng, R. Siegwart
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引用次数: 35

Abstract

Cloud Robotics is currently driving interest in both academia and industry. It allows different types of robots to share information and develop new skills even without specific sensors. They can also perform intensive tasks by combining multiple robots with a cooperative manner. Multi-sensor data retrieval is one of the fundamental tasks for resource sharing demanded by Cloud Robotic system. However, many technical challenges persist, for example Multi-Sensor Data Retrieval (MSDR) is particularly difficult when Cloud Cluster Hosts accommodate unpredictable data requested by multi robots in parallel. Moreover, the synchronization of multi-sensor data mostly requires near real-time response of different message types. In this paper, we describe a MSDR framework which is comprised of priority scheduling method and buffer management scheme. It is validated by assessing the quality of service (QoS) model in the sense of facilitating data retrieval management. Experiments show that the proposed framework achieves better performance in typical Cloud Robotics scenarios.
云机器人系统中多传感器信息的实时检索
云机器人目前在学术界和工业界都引起了人们的兴趣。它允许不同类型的机器人共享信息并开发新技能,即使没有特定的传感器。他们还可以通过合作的方式组合多个机器人来执行密集的任务。多传感器数据检索是云机器人系统资源共享的基本任务之一。然而,许多技术挑战仍然存在,例如,当云集群主机并行容纳多个机器人请求的不可预测数据时,多传感器数据检索(MSDR)尤其困难。此外,多传感器数据的同步大多需要不同消息类型的近实时响应。本文描述了一个由优先级调度方法和缓冲区管理方案组成的MSDR框架。通过评估服务质量(QoS)模型,从便于数据检索管理的角度对其进行验证。实验表明,该框架在典型的云机器人场景下取得了较好的性能。
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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