Inferring Context and Goals for Online Human-Aware Planning

Abstract

Planning for robots in environments co-inhabited by humans entails handling exogenous events during plan execution. Such events require plans to be continuously adapted to ensure that they remain "human-aware", i.e., adherent to human preferences and needs. We use an approach whereby human-awareness is enforced through so-called interaction constraints. Interaction constraints are used to infer context and appropriate goals online. The current plan is modified at run time so as to achieve courses of action that are continuously human-aware. The approach is evaluated in a research facility environment in which we simulate multiple days of planning and execution.