  Mobile robots are increasingly populating homes, hospitals, shopping malls,
factory floors, and other human environments. Human society has social norms
that people mutually accept; obeying these norms is an essential signal that
someone is participating socially with respect to the rest of the population.
For robots to be socially compatible with humans, it is crucial for robots to
obey these social norms. In prior work, we demonstrated a Socially-Aware
Navigation (SAN) planner, based on Pareto Concavity Elimination Transformation
(PaCcET), in a hallway scenario, optimizing two objectives so that the robot
does not invade the personal space of people. This paper extends our PaCcET
based SAN planner to multiple scenarios with more than two objectives. We
modified the Robot Operating System's (ROS) navigation stack to include PaCcET
in the local planning task. We show that our approach can accommodate multiple
Human-Robot Interaction (HRI) scenarios. Using the proposed approach, we
achieved successful HRI in multiple scenarios like hallway interactions, an art
gallery, waiting in a queue, and interacting with a group. We implemented our
method on a simulated PR2 robot in a 2D simulator (Stage) and a pioneer-3DX
mobile robot in the real-world to validate all the scenarios. A comprehensive
set of experiments shows that our approach can handle multiple interaction
scenarios on both holonomic and non-holonomic robots; hence, it can be a viable
option for a Unified Socially-Aware Navigation (USAN).
