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Plug'n Play Task-Level Autonomy for Robotics Using POMDPs and Probabilistic Programs

Or Wertheim,Dan R. Suissa,R. Brafman

Published 2024 in IEEE Robotics and Automation Letters

ABSTRACT

We describe AOS, the first general-purpose system for model-based control of autonomous robots using AI planning that fully supports partial observability and noisy sensing. The AOS provides a code-based language for specifying a generative model of the system, making model specification easier and model sampling efficient. It provides a language for specifying the relation between the model and the code, using which it auto-generates all required integration code. This allows Plug'n Play behavior, which facilitates incremental and modular system design. Extensive experiments on real and simulated robotic platforms demonstrate these advantages.

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