为机器人信息反馈策略设计最小必要结构，确保任务高效完成。
Minimally sufficient structures for information-feedback policies
- 基于滤波器与物理世界耦合，构建可实现任务的内部系统结构。
- 证明在弱假设下，特定计划对应的最小内部系统存在且唯一。
- 应用于多边形环境下的距离最优导航，验证结构有效性。
本文研究机器人在物理世界中达成目标的任务，需设计能保持世界有用表示的滤波器及基于滤波器状态的策略。滤波器是机器人在有限感知、记忆和计算下的世界表征，以信息状态上的转移系统形式表达。通过传感器映射和信息反馈策略，内部系统与外部物理世界相互作用。本文建立足够结构存在的充要条件，使得可在内部系统状态上定义信息反馈策略。在温和假设下，证明了描述动作-观测历史中特定计划的最小内部系统存在且唯一。最后，将结果应用于多边形环境中的距离最优导航，确定其所需充分结构。
原文摘要 · Abstract (English)
In this paper, we consider robotic tasks which require a desirable outcome to be achieved in the physical world that the robot is embedded in and interacting with. Accomplishing this objective requires designing a filter that maintains a useful representation of the physical world and a policy over the filter states. A filter is seen as the robot's perspective of the physical world based on limited sensing, memory, and computation and it is represented as a transition system over a space of information states. To this end, the interactions result from the coupling of an internal and an external system, a filter, and the physical world, respectively, through a sensor mapping and an information-feedback policy. Within this setup, we look for sufficient structures, that is, sufficient internal systems and sensors, for accomplishing a given task. We establish necessary and sufficient conditions for these structures to satisfy for information-feedback policies that can be defined over the states of an internal system to exist. We also show that under mild assumptions, minimal internal systems that can represent a particular plan/policy described over the action-observation histories exist and are unique. Finally, the results are applied to determine sufficient structures for distance-optimal navigation in a polygonal environment.
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