High-Level Description of Robot Architecture
This research provides a more generic and systematic conceptualization of architectural descriptions for robotic system designers, aiming to reduce inconsistencies and improve clarity in the early design phases.
This paper addresses the inconsistencies and lack of systematic approaches in current high-level architectural descriptions (ADs) for robotic systems. By applying the Thinging Machine (TM) modeling methodology, the authors re-express sample robot architectures to create static, dynamic, and behavioral models, demonstrating a viable approach to determine robot system behavior through static descriptions.
Architectural Description (AD) is the backbone that facilitates the implementation and validation of robotic systems. In general, current high-level ADs reflect great variation and lead to various difficulties, including mixing ADs with implementation issues. They lack the qualities of being systematic and coherent, as well as lacking technical-related forms (e.g., icons of faces, computer screens). Additionally, a variety of languages exist for eliciting requirements, such as object-oriented analysis methods susceptible to inconsistency (e.g., those using multiple diagrams in UML and SysML). In this paper, we orient our research toward a more generic conceptualization of ADs in robotics. We apply a new modeling methodology, namely the Thinging Machine (TM), to describe the architecture in robotic systems. The focus of such an application is on high-level specification, which is one important aspect for realizing the design and implementation in such systems. TM modeling can be utilized in documentation and communication and as the first step in the system s design phase. Accordingly, sample robot architectures are re-expressed in terms of TM, thus developing (1) a static model that captures the robot s atemporal aspects, (2) a dynamic model that identifies states, and (3) a behavioral model that specifies the chronology of events in the system. This result shows a viable approach in robot modeling that determines a robot system s behavior through its static description.