Socially-appropriate approach paths using human data

Abstract

For service robots operating in indoor environments, the crucial task of navigation is often complicated by the presence of people. Simply treating humans in the environment as additional (often moving) obstacles can violate the complex set of social rules by which people navigate around each other. In contrast, emulating human behavior and navigating in a socially appropriate manner could positively affect people's comfort with a robot's presence and motion. We present a method of generating social paths for a robot to approach a person based on a small amount of human data. We also conducted a study in which a robot approached participants using both these social paths and straight-line, nonsocial paths. We found that both approaches were rated comparably when the robot approached from the participant's front or side, but the social approach was significantly preferred when the robot came from behind the participant.