Managing the Functional Variability of Robotic Perception Systems

Control systems for autonomous robots are concurrent, distributed, embedded, real-time and data intensive software systems. A real-world robot control system is composed of tens of software components. For each component providing robotic functionality, tens of different implementations may be available. The difficult challenge in robotic system engineering consists in selecting acoherent set of components, which provide the functionality required by theapplication requirements, taking into account their mutual dependencies. This challenge is exacerbated by the fact that robotics system integrators andapplication developers are usually not specifically trained in softwareengineering. Current approaches to variability management in complex software systemsconsists in explicitly modeling variation points and variants in softwarearchitectures in terms of Feature Models. The novel contribution of this paper is the description of the integration oftwo modeling languages and toolkit, namelyHyperFlex for functional variability modeling and the Robot Perception Specification Language (RPSL), a Domain-specific Language (DSL) enabling domain experts to express the architectural variability of robotperception systems.