COMPANION: A Constraint-Optimizing Method for Person-Acceptable Navigation

摘要

This paper introduces the COMPANION framework: a constraint-optimizing method for person-acceptable navigation. In this framework, human social conventions, such as personal space and tending to one side of hallways, are represented as constraints on the robot's navigation. These constraints are accounted for at the global planning level. In this paper, we present the rationale for, and implementation of, this framework, and we describe the experiments we have run in simulation to verify that the method produces human-like behavior in a mobile robot. Our approach is novel in that it can express an arbitrary number of social conventions and explicitly accounts for these conventions in the planning phase.