WHY: Natural Explanations from a Robot Navigator
This addresses the need for better communication in human-robot teams, though it is incremental as it builds on existing navigation and language generation methods.
The paper tackles the problem of enabling robots to explain their navigation decisions in natural language to improve human-robot collaboration, resulting in a system that generates intuitive explanations in real-time for complex indoor environments.
Effective collaboration between a robot and a person requires natural communication. When a robot travels with a human companion, the robot should be able to explain its navigation behavior in natural language. This paper explains how a cognitively-based, autonomous robot navigation system produces informative, intuitive explanations for its decisions. Language generation here is based upon the robot's commonsense, its qualitative reasoning, and its learned spatial model. This approach produces natural explanations in real time for a robot as it navigates in a large, complex indoor environment.