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Item type:Publication, Access status: without files , Decentralized process learning for cyber-physical systemsThe application of robots in industries is increasing, and the complexity of modern robotic systems demands systematic and well-structured planning. There is a growing need for design approaches that provide both structure and the flexibility to explore alternative solutions early in the requirements and system design phases. Model-Based Systems Engineering offers such an approach by enabling the specification, analysis, and design of complex systems through the use of system models. However, current robot design approaches rarely consider kinematic properties during the requirements phase, which hinders evaluating whether the robot’s realistic capabilities that depend on the robot's kinematic capabilities align with the task requirements early in the design process. In this paper, we propose the use of system models for the specification of robot kinematic properties and demonstrate how these models can be used to evaluate robot capabilities against their requirements.Publicationtype: Conference Paper42