Executing Robot Task Models in Dynamic Environments

摘要

Deploying successful robotics applications requires tremendous effort due to the need for contributions of experts from various domains.We present the iserveU family of executable DSLs that separate the concerns of domain experts and robotics experts and leverage model-transformation at system run-time to enable the robotic platform to flexibly fulfill tasks in a changing real-world environment.Current research in DSLs for robotics applications focuses on abstraction in the solution domain, whereas our DSLs support the domain expert in declaratively describing properties of the domain and loosely coupled tasks.To enable flexible task execution based on the domain expert's declarative models, these are translated into components of a reference architecture prior to deployment and into planning domain definition language (PDDL) problems at system runtime.Resulting problems are translated into executable plans using the Metric-FF solver and re-translated into iserveU models that ultimately are executed against a loosely coupled robotics middleware.Leveraging model transformation at run-time enables the flexibility necessary for robotics applications deployed to dynamic environments where design-time assumptions and run-time reality diverge easily.