Reasoning Systems for Semantic Navigation in Mobile Robots

TL;DR

This paper develops and compares two semantic environment models for mobile robot navigation, integrating them into a semantic navigator and demonstrating their effectiveness through real-world implementation.

Contribution

It introduces two ontological models for semantic navigation, one using a relational database and the other based on KnowRob, and compares their performance.

Findings

Both systems successfully enable semantic navigation in robots.

The KnowRob-based system offers more flexible reasoning capabilities.

Quantitative and qualitative evaluations demonstrate the strengths of each approach.

Abstract

Semantic navigation is the navigation paradigm in which environmental semantic concepts and their relationships are taken into account to plan the route of a mobile robot. This paradigm facilitates the interaction with humans and the understanding of human environments in terms of navigation goals and tasks. At the high level, a semantic navigation system requires two main components: a semantic representation of the environment, and a reasoner system. This paper is focused on develop a model of the environment using semantic concepts. This paper presents two solutions for the semantic navigation paradigm. Both systems implement an ontological model. Whilst the first one uses a relational database, the second one is based on KnowRob. Both systems have been integrated in a semantic navigator. We compare both systems at the qualitative and quantitative levels, and present an implementation on a mobile robot as a proof of concept.