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 planner/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.

中文翻译：

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可插拔分布式资源分配器 (PDRA)：移动机器人网络中分布式计算的中间件

我们提出了可插拔分布式资源分配器 (PDRA)，这是一种用于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，用于计算昂贵的任务，例如定位和路径规划。它位于现有的单代理规划器/执行器和现有计算资源（例如 ROS 包）之间，拦截执行器的请求，并在需要时透明地将它们路由到其他机器人执行。PDRA 是可插拔的：它可以通过最少的修改集成到现有的单机器人自主堆栈中。任务分配决策由混合整数编程算法执行，以共享世界的方式解决，该算法对 CPU 资源、延迟要求以及多跳、周期性、带宽受限的网络通信；该算法可以最大限度地减少整体能源使用或最大化完成可选任务的奖励。仿真结果表明，在典型的多机器人场景中，PDRA 可以比单纯的调度器减少 50% 以上的能量和 CPU 使用率；在嵌入式平台上运行；并且在延迟和中断容忍网络 (DTN) 中表现良好。PDRA 在开源许可下提供给社区。