  A robot guide dog has compelling advantages over animal guide dogs for its
cost-effectiveness, potential for mass production, and low maintenance burden.
However, despite the long history of guide dog robot research, previous studies
were conducted with little or no consideration of how the guide dog handler and
the guide dog work as a team for navigation. To develop a robotic guiding
system that is genuinely beneficial to blind or visually impaired individuals,
we performed qualitative research, including interviews with guide dog handlers
and trainers and first-hand blindfold walking experiences with various guide
dogs. Grounded on the facts learned from vivid experience and interviews, we
build a collaborative indoor navigation scheme for a guide dog robot that
includes preferred features such as speed and directional control. For
collaborative navigation, we propose a semantic-aware local path planner that
enables safe and efficient guiding work by utilizing semantic information about
the environment and considering the handler's position and directional cues to
determine the collision-free path. We evaluate our integrated robotic system by
testing guide blindfold walking in indoor settings and demonstrate guide
dog-like navigation behavior by avoiding obstacles at typical gait speed ($0.7
\mathrm{m/s}$).
