  The popularity of mobile robots has been steadily growing, with these robots
being increasingly utilized to execute tasks previously completed by human
workers. For bipedal robots to see this same success, robust autonomous
navigation systems need to be developed that can execute in real-time and
respond to dynamic environments. These systems can be divided into three
stages: perception, planning, and control. A holistic navigation framework for
bipedal robots must successfully integrate all three components of the
autonomous navigation problem to enable robust real-world navigation. In this
paper, we present a real-time navigation framework for bipedal robots in
dynamic environments. The proposed system addresses all components of the
navigation problem: We introduce a depth-based perception system for obstacle
detection, mapping, and localization. A two-stage planner is developed to
generate collision-free trajectories robust to unknown and dynamic
environments. And execute trajectories on the Digit bipedal robot's walking
gait controller. The navigation framework is validated through a series of
simulation and hardware experiments that contain unknown environments and
dynamic obstacles.
