Constraint-Based Online Transformation of Abstract Plans into Executable Robot Actions

In this paper, we are concerned with making the execution of abstract action plans for robotic agents more robust. To this end, we propose to model the internals of a robot system and its ties to the actions that the robot can perform. Based on these models, we propose an online transformation of an abstract plan into executable actions conforming with system specifics. With our framework, we aim to achieve two goals. First, modeling the system internals is beneficial in its own right in order to achieve long term autonomy, system transparency, and comprehensibility. Second, separating the system details from determining the course of action on an abstract level leverages the use of planning for actual robotic systems.