Abstracting Noisy Robot Programs

Till Hofmann; Vaishak Belle

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arXiv · 2204.03536

Abstracting Noisy Robot Programs

Till Hofmann·Vaishak Belle

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Abstract

Abstraction is a commonly used process to represent some low-level system by a more coarse specification with the goal to omit unnecessary details while preserving important aspects. While recent work on abstraction in the situation calculus has focused on non-probabilistic domains, we describe an approach to abstraction of probabilistic and dynamic systems. Based on a variant of the situation calculus with probabilistic belief, we define a notion of bisimulation that allows to abstract a detailed probabilistic basic action theory with noisy actuators and sensors by a possibly non-stochastic basic action theory. By doing so, we obtain abstract Golog programs that omit unnecessary details and which can be translated back to a detailed program for actual execution. This simplifies the implementation of noisy robot programs, opens up the possibility of using non-stochastic reasoning methods (e.g., planning) on probabilistic problems, and provides domain descriptions that are more easily understandable and explainable.

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Till Hofmann, Vaishak Belle. 2022-04-07. Abstracting Noisy Robot Programs. https://arxiv.org/abs/2204.03536

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