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The Pluggable Distributed Resource Allocator (PDRA): a Middleware for Distributed Computing in Mobile Robotic Networks

机译:可插拔分布式资源分配器(PDRA):用于移动机器人网络中分布式计算的中间件

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We present the Pluggable Distributed Resource Allocator (PDRA), a middleware for distributed computing in heterogeneous mobile robotic networks. PDRA enables autonomous robotic agents to share computational resources for computationally expensive tasks such as localization and path planning. It sits between an existing single-agent plan- ner/executor and existing computational resources (e.g. ROS packages), intercepts the executor's requests and, if needed, transparently routes them to other robots for execution. PDRA is pluggable: it can be integrated in an existing single-robot autonomy stack with minimal modifications. Task allocation decisions are performed by a mixed-integer programming algorithm, solved in a shared-world fashion, that models CPU resources, latency requirements, and multi-hop, periodic, bandwidth-limited network communications; the algorithm can minimize overall energy usage or maximize the reward for completing optional tasks. Simulation results show that PDRA can reduce energy and CPU usage by over 50% in representative multi-robot scenarios compared to a naive scheduler; runs on embedded platforms; and performs well in delay- and disruption-tolerant networks (DTNs). PDRA is available to the community under an open-source license.
机译:我们介绍了可插拔分布式资源分配器(PDRA),用于在异构移动机器人网络中分布式计算的中间件。 PDRA使自主机器人代理能够共享计算资源,以便计算昂贵的任务,如本地化和路径规划。它位于现有的单次代理计划和执行者和现有的计算资源(例如ROS包)之间,拦截执行器的请求,如果需要,透明地将它们路由到其他机器人以进行执行。 PDRA可插拔:它可以集成在现有的单机器人自主堆栈中,修改最小。任务分配决策由混合整数编程算法执行,以共享世界时尚解决,模拟CPU资源,延迟要求和多跳,周期性,带宽限制网络通信;该算法可以最大限度地减少整体能量使用或最大化完成可选任务的奖励。仿真结果表明,与天真调度器相比,PDRA可以将能源和CPU使用率降低超过50%的代表多机器人场景;在嵌入式平台上运行;并且在延迟和破坏宽容网络(DTN)中表现良好。在开源许可证下社区提供PDRA。

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