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(WIP) At Most M - A Flexible Redundancy Model for Cloud Robotics

机译:(WIP)至多M-云机器人的灵活冗余模型

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The current trend in industry to augment lightweight and inexpensive robots with cloud-based distributed intelligence for executing complex, collaborative tasks has led to the emergence of fields like Internet of Robotic Things (IoRT) and Cloud Robotics (CR). However, reliable execution of orchestrated jobs in a networked setup with chances of infrastructural failures remains a concern. The only perceivable solution is resource redundancy, where the traditional approaches are not cost effective for tightly budgeted IoRT/CR deployments. In this work, an agile redundancy model, At most M, is proposed, which provides a handle to tune the trade-off between resource cost and reliability. The model is evaluated in a simulated warehouse environment with robots, drones, AGVs and private cloud servers deployed to accomplish multiple pickup and delivery tasks. The benefits w.r.t. resource usage cost by using our optimized redundancy model is illustrated and the trade-off between cost and reliability is demonstrated.
机译:当前的行业趋势是,通过基于云的分布式智能来增强轻巧,廉价的机器人来执行复杂的协作任务,导致出现了诸如机器人物联网(IoRT)和云机器人(CR)之类的领域。但是,在网络设置中可靠地执行精心安排的作业并可能发生基础设施故障的可能性仍然值得关注。唯一可察觉的解决方案是资源冗余,在这种情况下,传统方法对于预算紧张的IoRT / CR部署而言并不划算。在这项工作中,提出了一个敏捷的冗余模型(最多M),该模型提供了一种在资源成本和可靠性之间进行权衡取舍的方法。该模型是在模拟仓库环境中进行评估的,该环境中部署了机器人,无人机,AGV和私有云服务器以完成多个提货和交付任务。好处通过使用我们的优化冗余模型说明了资源使用成本,并说明了成本与可靠性之间的权衡。

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