Ontology-based knowledge management with verbal interaction for command interpretation and execution by home service robots

This paper describes a system for service robots that combines ontological knowledge reasoning and human-robot interaction to interpret natural language commands and successfully perform household chores, such as finding and delivering objects. Knowledge and context reasoning is essential for providing more efficient service robots, given their diverse and continuously changing environments. Moreover, since they are in contact with humans, robots require such skills as interaction and language. Therefore, we developed a system with specific modules to manage robots' knowledge and reasoning, command analysis, decision-making, and talking interaction. The system relies on inference methods and verbal interaction to understand commands and clarify uncertain information. We tested our system inside a simulated environment where the robot receives commands with missing or unclear information. The system's performance was compared with the average performance of human subjects who completed the same commands in the simulation. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper presents a system for service robots that combines ontological knowledge reasoning and human-robot interaction to interpret natural language commands. The system's performance was compared with human subjects in a simulated environment, showing comparable results.