Dynamic Allocation of Service Robot Resources to an Order Picking Task Considering Functional and Non-Functional Properties

Timo Blender, C. Schlegel
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引用次数: 1

Abstract

Industry 4.0 processes have often varying requirements. A service robot and a team of service robots respectively represent a flexible resource. That means, it possesses variability that can possibly be configured in such a way that it is able to fulfill the requirements of industry 4.0 processes. Determining whether that is the case and how that has to happen is an important part of variability management. Based on a model-driven general method for variability management in a robotics software ecosystem, we present here a concrete use case (model) in which we allocate for an order picking task with specific time requirements either a single fitting service robot or a collaboration of two fitting service robots. Relevant properties of the service robots considered are both functional (are the capabilities to execute the tasks available?) as well as non-functional (the desired velocity parameterization while executing the individual navigation sub tasks limited by the respective maximum speed of a service robot).
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考虑功能和非功能特性的服务机器人拣货任务资源动态分配
工业4.0过程通常有不同的要求。一个服务机器人和一个服务机器人团队分别代表一种柔性资源。这意味着,它具有可变性,可以以能够满足工业4.0流程要求的方式进行配置。确定情况是否如此以及如何发生是可变性管理的一个重要部分。基于机器人软件生态系统中可变性管理的模型驱动通用方法,我们在这里提出了一个具体的用例(模型),其中我们为具有特定时间要求的订单挑选任务分配单个装配服务机器人或两个装配服务机器人的协作。所考虑的服务机器人的相关属性既有功能性的(执行任务的能力是否可用?),也有非功能性的(在执行受服务机器人各自最大速度限制的单个导航子任务时所需的速度参数化)。
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