Context-aware Social Robot Navigation

Abstract

With the emergence of robots being deployed in unstructured environments outside the industrial domain, the importance of robots behaving appropriately in the vicinity of people is becoming more clear. These behaviours are hard to model as they depend on the social context. This context includes among other things where the robot is deployed, how crowded that place is, as well as who are residing in that place. In this paper we extend social space theory with the social context, making them adaptable to the current situation. We implement the social spaces as costmaps used in the standard ROS navigation stack. Our method - Context-Aware Social robot Navigation (CASN) - is tested in the context of people avoidance in social navigation. We compare CASN with the social navigation layer package, which also implements costs based on detected people. We show that by using CASN a mobile robot complies with social conventions in four different navigation scenarios.