Integrating planning and execution for ROS enabled service robots using hierarchical action representations

The aim of the RoboEarth project is to develop a globally accessible database, that enables service robots to share reusable information relevant to the execution of their daily tasks. Examples of this information are the hierarchical task descriptions, or action recipes, that represent typical household tasks as symbolic action sequences. By annotating these static action representations with hierarchical planner predicates, they can be interpreted by a Hierarchical Task Network planner such as SHOP2 to compose optimized robot plans in a flexible manner, based on the actual state of the environment and the available capabilities of the robot. To subsequently execute these plans in a household environment, the CRAM executive toolbox is adopted, allowing a tight integration between plan execution and the run-time inference of dynamically updated environment knowledge. This paper presents the integration of these two planning and execution components into one cohesive framework, tailored for the safe execution of abstract tasks in challenging household environments. The resulting framework is implemented on the AMIGO service robot and a basic experiment is conducted to demonstrate the frameworks integral functionality.