  In this paper, we propose a novel navigation system for mobile robots in
pedestrian-rich sidewalk environments. Sidewalks are unique in that the
pedestrian-shared space has characteristics of both roads and indoor spaces.
Like vehicles on roads, pedestrian movement often manifests as linear flows in
opposing directions. On the other hand, pedestrians also form crowds and can
exhibit much more random movements than vehicles. Classical algorithms are
insufficient for safe navigation around pedestrians and remaining on the
sidewalk space. Thus, our approach takes advantage of natural human motion to
allow a robot to adapt to sidewalk navigation in a safe and socially-compliant
manner. We developed a \textit{group surfing} method which aims to imitate the
optimal pedestrian group for bringing the robot closer to its goal. For
pedestrian-sparse environments, we propose a sidewalk edge detection and
following method. Underlying these two navigation methods, the collision
avoidance scheme is human-aware. The integrated navigation stack is evaluated
and demonstrated in simulation. A hardware demonstration is also presented.
