  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.
