Reasoning-Based Evaluation of Manipulation Actions for Efficient Task Planning

To cope with the growing complexity of manipulation tasks, the way to combine and access information from high- and low-planning levels has recently emerged as an interesting challenge in robotics. To tackle this, the present paper first represents the manipulation problem, involving knowledge about the world and the planning phase, in the form of an ontology. It also addresses a high-level and a low-level reasoning processes, this latter related with physics-based issues, aiming to appraise manipulation actions and prune the task planning phase from dispensable actions. In addition, a procedure is contributed to run these two-level reasoning processes simultaneously in order to make task planning more efficient. Eventually, the proposed planning approach is implemented and simulated through an example.