A Representation for Spatial Reasoning in Robotic Planning

In order to close the sense-plan-act loop, a robot requires several capabilities: it must match perceived context with general knowledge about the environment, instantiate plans into the metric space of the real world, and detect and react to contingencies. All of these capabilities include some form of spatial reasoning — however, at different levels of abstraction. Perception generates metric spatial knowledge, while general knowledge about the environment is often qualitative in nature. Similarly, plans may call for the achievement of qualitative spatial relations, but actions must be precisely instantiated in metric space. This paper focuses on integrating qualitative and metric spatial reasoning for closing the loop around perception and actuation. We propose a knowledge representation and reasoning technique, grounded on wellestablished spatial calculi, for combining qualitative and metric knowledge and obtaining solutions expressed in actionable metric terms.