This paper describes an integrated solution to the problem of describing and interpreting goals for robots in open uncertain domains. Given a formal specification of a desired situation, in which objects are described only by their properties, general-purpose planning and reasoning tools are used to derive appropriate actions for a robot. These goals are carried out through an online combination of hierarchical planning, state-estimation, and execution that operates robustly in real robot domains with substantial occlusion and sensing error.
翻译:本文描述了在开放的不确定域描述和解释机器人目标的综合解决方案。 鉴于对理想状态的正式说明,即物体只能以其特性来描述,一般用途规划和推理工具被用于为机器人制定适当的行动。 这些目标是通过分级规划、国家估计和执行的在线组合来实现的,这些组合在真实的机器人域中运行得稳健,存在重大隔离和感测错误。