Situation-Aware Interpretation, Planning and Execution of User Commands by Autonomous Robots

For a robot to be able to first understand and then achieve a human's goals, it must be able to reason about a) the context of the current situation (with respect to which it must interpret the human's commands) and b) the future world state (as intended by the human) and how to achieve it. Since humans express their intentions and plans using qualitative symbolic representations, robots must be enabled to reason and interact on the same representational level. In this paper, we describe the use of classical AI planning techniques for situation-aware interpretation and execution of human commands. We show how, based on a planning domain, a robot can be enabled to understand commands in natural language, plan for their situation-dependent realization and revise its plans based on new perceptions. We show the effectiveness of this approach in several HRI scenarios modeled as planning domains as well as with examples from a real robot system developed in the EU-funded CoSy project.