Dynamic process migration in heterogeneous ROS-based environments

José Cano, Eduardo J. Molinos, V. Nagarajan, S. Vijayakumar
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引用次数: 10

Abstract

In distributed (mobile) robotics environments, the different computing substrates offer flexible resource allocation options to perform computations that implement an overall system goal. The AnyScale concept that we introduce and describe in this paper exploits this redundancy by dynamically allocating tasks to appropriate substrates (or scales) to optimize some level of system performance while migrating others depending on current resource and performance parameters. In this paper, we demonstrate this concept with a general ROS-based infrastructure that solves the task allocation problem by optimising the system performance while correctly reacting to unpredictable events at the same time. Assignment decisions are based on a characterisation of the static/dynamic parameters that represent the system and its interaction with the environment. We instantiate our infrastructure on a case study application, in which a mobile robot navigates along the floor of a building trying to reach a predefined goal. Experimental validation demonstrates more robust performance (around a third improvement in metrics) under the Anyscale implementation framework.
基于ros的异构环境中的动态流程迁移
在分布式(移动)机器人环境中,不同的计算基板提供灵活的资源分配选项,以执行实现整体系统目标的计算。我们在本文中介绍和描述的AnyScale概念通过动态地将任务分配到适当的基板(或规模)来优化某些级别的系统性能,同时根据当前资源和性能参数迁移其他级别的系统性能,从而利用这种冗余。在本文中,我们用一个通用的基于ros的基础设施来演示这个概念,该基础设施通过优化系统性能来解决任务分配问题,同时正确地对不可预测的事件做出反应。分配决策是基于代表系统及其与环境的相互作用的静态/动态参数的特征。我们在一个案例研究应用程序上实例化了我们的基础设施,在这个应用程序中,一个移动机器人沿着建筑物的楼层导航,试图达到一个预定义的目标。在Anyscale实现框架下,实验验证证明了更稳健的性能(大约三分之一的度量改进)。
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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