  As more robots are being deployed into human environments, a human-aware
navigation planner needs to handle multiple contexts that occur in indoor and
outdoor environments. In this paper, we propose a tunable human-aware robot
navigation planner that can handle a variety of humanrobot contexts. We present
the architecture of the planner and discuss the features and some
implementation details. Then we present a detailed analysis of various
simulated humanrobot contexts using the proposed planner along with some
quantitative results. Finally, we show the results in a real-world scenario
after deploying our system on a real robot.
