Software Product Line Engineering for Robotic Perception Systems

Abstract

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 a coherent set of components, which provide the functionality required by the application requirements, taking into account their mutual dependencies. This challenge is exacerbated by the fact that robotics system integrators and application developers are usually not specifically trained in software engineering. In various application domains, software product line (SPL) development has proven to be the most effective approach to face this kind of challenges. In a previous paper [D. Brugali and N. Hochgeschwender, Managing the functional variability of robotic perception systems, in First IEEE Int. Conf. Robotic Computing, 2017, pp. 277–283.] we have presented a model-based approach to the development of SPL for robotic perception systems, which integrates two modeling technologies developed by the authors: The HyperFlex toolkit [L. Gherardi and D. Brugali, Modeling and reusing robotic software architectures: The HyperFlex toolchain, in IEEE Int. Conf. Robotics and Automation, 2014, pp. 6414–6420.] and the Robot Perception Specification Language (RPSL) [N. Hochgeschwender, S. Schneider, H. Voos and G. K. Kraetzschmar, Declarative specification of robot perception architectures, in 4th Int. Conf. Simulation, Modeling, and Programming for Autonomous Robots, 2014, pp. 291–302.]. This paper extends our previous work by illustrating the entire development process of an SPL for robot perception systems with a real case study.

Software variability in service robotics

“…The studied papers aim at promoting the adoption of effective software engineering methods for developing robotics software. Papers from Table 6 discuss engineering paradigms such as Model-Driven Engineering (MDE) (Brugali and Gherardi 2016;Goldsby and Cheng 2008;Silva et al 2013), Software Product Line Engineering (Brugali and Hochgeschwender 2018;Lotz et al 2013), Software Frameworks (Kimour et al 2009), and Component-Based Software Engineering (Niemczyk and Geihs 2015). A few papers address the interplay of the various drivers of variability in robotics and propose approaches for their effective management.…”

Reutilización de software en la robótica industrial: un mapeo sistemático

“…Generalmente, estas nuevas contribuciones se prueban mediante un estudio de caso y más adelante, si esta es válida, las empresas adoptan estas aportaciones y las llevan al contexto de la industria. Por otro lado, es difícil encontrar empresas que inviertan directamente en investigación, aunque, hay casos específicos en los que las fábricas desarrollan una línea de productos software de aplicaciones robóticas para brazos industriales (Brugali and Hochgeschwender, 2018). La reutilización de software en el dominio de los robots industriales a nivel de empresa (industria) ha sido dominado por los enfoques MDE y CBSE, siendo los enfoques más utilizados y con mayor evidencia empírica de investigación.…”

Geração de Código para Robôs implementados com ROS a partir de modelos UML/MARTE

“…Uma outra abordagem baseada em MDE foi proposta em [16] para o projeto de linhas de produtos de software para sistemas de percepção de robôs. A abordagem sugere o uso de uma DSL chamada Robot Perception Specification Language que, por sua vez, não é uma linguagem de especificação padrão, o que acaba dificultando a adoção da abordagem proposta.…”