Integrating the planning, execution and monitoring systems for a domestic service robot

Embodied artificial agents operating in dynamic, real-world environments need architectures that support the special requirements that exist for them. Architectures are not always designed from scratch and the system then implemented all at once, but rather, a step-wise integration of components is often made to increase functionality. Our work aims to increase flexibility and robustness by integrating a task planner into an existing architecture and coupling the planning process with the preexisting execution and the basic monitoring processes. This involved the conversion of monolithic SMACH scenario scripts (state-machine execution scripts) into modular states that can be called dynamically based on the plan that was generated by the planning process. The procedural knowledge encoded in such state machines was used to model the planning domain for two RoboCup@Home scenarios on a Care-O-Bot 3 robot [GRH+08]. This was done for the JSHOP2 [IN03] hierarchical task network (HTN) planner. A component which iterates through a generated plan and calls the appropriate SMACH states [Fie11] was implemented, thus enabling the scenarios. Crucially, individual monitoring actions which enable the robot to monitor the execution of the actions were designed and included, thus providing additional robustness