Ontology-Based Unified Robot Knowledge for Service Robots in Indoor Environments

Abstract

Abstract-A significant obstacle for service robots is the execution of complex tasks in real environments. For example, it is not easy for service robots to find objects that are partially observable and are located at a place which is not identical but near the place where the robots saw them previously. To overcome the challenge effectively, robot knowledge represented as a semantic network can be extremely useful. This paper presents an ontology-based unified robot knowledge framework that integrates low-level data with high-level knowledge for robot intelligence. This framework consists of two sections: knowledge description and knowledge association. Knowledge description includes comprehensively integrated robot knowledge derived from low-level knowledge regarding perceptual features, part objects, metric maps, and primitive behaviors, as well as high-level knowledge about perceptual concepts, objects, semantic maps, tasks, and contexts. Knowledge association uses logical inference with both unidirectional and bidirectional rules. This characteristic enables reasoning to be performed even when only a partial information is available. The experimental results that demonstrate the advantages of using the proposed knowledge framework are also presented.Index Terms-Intelligent service robot, knowledge association, knowledge description, ontology-based knowledge, unified robot knowledge.

Extensions to the core ontology for robotics and automation

“…Other ontologies can also be integrated with our ontologies, providing a wide range of concepts and relations that allow richer descriptions of the robot's world. Such semantic descriptions can be used by the robot in perception processes such as [19][20][21][22] for enhancing tasks that require object recognition through visual perception. These semantic descriptions can be used also for specifying tasks to the robot, as in [23].…”

Grounding the Interaction: Knowledge Management for Interactive Robots

“…The Ontology-based Unified Robot Knowledge [82] (OUR-K) framework, successor of the Ontology-based Multi-layered Robot Knowledge Framework [128] (OMRKF), is a knowledge representation system based on five inter-related classes of knowledge (figure 2.8). It proposes a layered approach to knowledge representation that allows to integrate the grounding process to the knowledge representation process.…”

World Modeling for Autonomous Systems

“…Within a world model for autonomous systems, semantics, i.e. the meaning of symbols received from sensors or humans, have to be introduced in one or another way (Lim et al (2011)). When preparing a system for operation, it is possible to equip the system with definitions of all the relevant concepts that are supposed to be encountered within its operational tasks.…”