Socially Aware Robot Navigation Framework: Where and How to Approach People in Dynamic Social Environments

This paper proposes a human approaching robot navigation framework that enables a mobile service robot to (i) estimate a socially optimal approaching pose, and (ii) navigate safely and socially to the estimated approaching pose. In the first stage, the robot estimates potential approaching poses of a human or a human group, which the robot can safely and socially approach, using the dynamic social zone model. In the second stage, the proposed framework selects a socially optimal approaching pose, then estimate a socially optimal trajectory of the robot using the proposed goal-oriented timed elastic band (GTEB) model. The developed GTEB model takes into account the current robot's states, robot dynamics, dynamic social zone, regular obstacles and potential approaching poses to generate the socially optimal robot trajectory from the robot's current pose to the selected optimal approaching pose. The motion control command extracted from the socially optimal trajectory is then utilized to drive the mobile robot to approach the individual humans or human groups, while safely and socially avoiding regular obstacles, human and human groups during the navigation process. The proposed approaching human framework is verified in the both simulation and real robots. The results illustrate that, the mobile robot equipped with our developed GTEB model is able to safely and socially approach and avoid individual humans and human groups, while guaranteeing the comfortable safety for the humans and socially acceptable behaviors for the robot.