Knowledge-Based Reasoning on Semantic Maps
Roberto Capobianco, Guglielmo Gemignani, Daniele Nardi, Domenico D. Bloisi, Luca Iocchi · 2014
Robotic systems should have a deep and specific knowl-edge about the environment they live in to properly in-teract with people and effectively perform the requested tasks. To this end, a suitable representation of the en-vironment is needed, including both metric spatial in-formation and semantic representations of locations and objects of interest. In this paper a representation of spa-tial and environmental knowledge, as well as a method for reasoning on it are presented. More specifically, the representation method is designed to properly integrate metric information about the environment and semantic information provided by the user, allowing for an effec-tive knowledge-based reasoning. The result is a quali-tative high-level representation of the environment that embodies all the knowledge required by a robot to actu-ally reason on it and execute complex tasks.