Dynamic allocation of service robot resources to an order picking task considering functional and non-functional properties

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).