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Low latency bounty hunting and geographically adjacent server configuration for real-time cloud control

机译:低延迟赏金搜寻和地理位置相邻的服务器配置,用于实时云控制

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This paper explores the feasibility and proposes a method on how to obtain high frequency real-time controllers operating in loop with physical robot hardware over a geographically adjacent and bounty hunting cloud server architecture. Having the cloud in the loop has many purposes including increasing computation, decreasing ???on robot??? power usage, reducing overall robot weight etc. Today when robots use the cloud in loop it is typically for sharing information, high level planning, and other non-real-time tasks. All of the balancing and stability algorithms stay onboard the robot. What if we could run high frequency real-time loops over the cloud? The better question is how would we do that? As with any real-time system latency is a big factor in the application and operation frequency. This paper shows that with a geographically adjacent and bounty hunting server approach it is feasible to obtain high frequency real-time control in loop with with a physical robot over the cloud. The feasibility of such a system running in-loop on humanoids and wheeled robots are explored and tested.
机译:本文探讨了可行性,并提出了一种方法,该方法可获取如何在地理位置相邻且赏金打猎的云服务器架构上与物理机器人硬件循环运行的高频实时控制器。使云处于循环中具有许多目的,包括增加计算量,减少“在机器人上”量。如今,当机器人循环使用云时,通常用于共享信息,高级计划和其他非实时任务。所有平衡和稳定性算法都保留在机器人上。如果我们可以在云上运行高频实时循环该怎么办?更好的问题是我们将如何做?与任何实时系统一样,延迟是影响应用程序和操作频率的重要因素。本文表明,使用地理上相邻且有赏金的狩猎服务器方法,使用物理机器人在云端循环获得高频实时控制是可行的。探索并测试了这种系统在类人动物和轮式机器人上循环运行的可行性。

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