Browsing by Subject "variability management"

This thesis introduces Robot Configurator, a software for performing variability configuration for a robot cooperation software named Cooperative Brain Service. The variability configuration problem concerns selecting appropriate combinations of components to form a valid complete product. It is applicable to the realm of software as well, as there are approaches where an instance of software is formed from different pre-made components. Cooperative Brain Service is the main product of Creative and Adaptive Cooperation between Diverse Autonomous Robots (CACDAR), a University of Helsinki research project. One of the main principles of the project is enabling cooperation between various types of robots. In Cooperative Brain Service, this is taken into account by having support for any new robots and actions be added as new modules. In the current implementation, the modules to be loaded are determined during startup, through a manually written JSON configuration file. The problem is, managing such JSON files requires beforehand knowledge of what modules there are implemented in Cooperative Brain Service. As it is crucial to be able to flexibly experiment with different cooperation scenarios in CACDAR, I design Robot Configurator as a tool to assist in the creation and management of these JSON configuration files. The main contribution of this thesis is Robot Configurator, for which I provide an architecture description that describes and documents it from multiple stakeholder perspectives. Additionally, a novel approach to modeling variability involved in the initialization of Cooperative Brain Service is also introduced.