Robots in Crowds — Being Useful While Staying Out of Trouble

In this paper we are considering an autonomous robot moving purposefully in a crowd of people (a marketplace). The robot should take into consideration the social costs of its movement, expressed in terms of violation of the personal space of the humans, blocking their path or even making physical contact with them. On the other hand, the full avoidance of any social cost might jeopardize the mission of the robot in a sufficiently dense crowd, movement is impossible without violating at least some social norms. The individuals in the crowd, including the robot, periodically encounter micro-conflicts where they need to change their behavior to avoid large social costs (such as bumping into each other). We model the resolution of micro-conflicts as a series of games where the payoffs integrate the social and mission costs of the action choices. We show that human behavior corresponds to a strategy which is not necessarily optimal on a single-game basis; instead, it reflects the personality and social status of the person and the psychological requirement of consistency in behavior. We describe a robot behavior which classifies the strategy used by the opponent in the micro-conflict and chooses an appropriate counter-strategy which takes into account the urgency of the robot’s mission.