Abstract :
[en] As robots are becoming ubiquitous and more capable, the need for introducing solid robot software development methods is pressing to increase robots' task spectrum.
This thesis is concerned with improving software engineering of robot perception systems. The presented research employs a model-based approach to provide the means to represent knowledge about robotics software. The thesis is divided into three parts, namely research on the specification, deployment and adaptation of robot perception systems.
The first part contributes the design and development of two domain-specific languages, namely RPSL and DepSL. Those languages provide suitable notations and abstractions to enable domain experts to express, compose and explore functional, architectural and deployment design decisions of robot perception systems. The resulting models are interpretable, thus they can be used not only to communicate design decisions to stakeholders, but also to verify them in an early development stage.
The second part contributes means for deploying perception systems on real robot systems even in the presence of varying resource conditions. To this end, functional, architectural and deployment models are composed in a graph-structure. Such a graph enables not only humans, but also robots to derive implicitly defined information about their software both at design time and run time. The second part also contributes a reference architecture for deploying robot perception systems. The architecture provides a template solution for integrating not only the models required for deployment, but also all the other means required to carry out deployment.
The third part utilizes both RPSL, DepSL and the reference architecture to specify, implement and evaluate three different robot perception systems. Those are capable to satisfy changing requirements induced, for example, by the robot's tasks or environment. This is achieved by proposing algorithms which derive adaptation actions based on models and varying requirements.
