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arXiv Robotics — research abstracts· Aalap D. Shah, Basil Saeed, Joshua B. Tenenbaum, Tobias Gerstenberg, Hyowon Gweon, Ilker Yildirim·· 2 days agoSignalEditorial score75

A computational framework for understanding embodied plans

A computational framework for understanding embodied plans

Summary

This research presents GenEA, a novel agent representation that reasons over multi-step, long-horizon embodied plans by coupling coarse biomechanics of an articulated body with interactions using simulation-based intuitive physics. Embedded in a generative model, GenEA yields a joint probability distribution over goals and embodied plans. Experiments across object manipulation and navigation show that GenEA recapitulates human reasoning about embodied plans through simple transformations of this distribution and consistently outperforms strong alternatives including plausible heuristics, standard task-and-motion planning, and state-of-the-art vision-language models.

Editorial context

The paper introduces GenEA, a generative agent model that couples articulated biomechanics with intuitive physics to reason about multi-step embodied plans, demonstrating superior performance over heuristics, standard task-and-motion planning, and vision-language models in object manipulation and navigation tasks.

Source: arXiv Robotics — research abstracts · Read original article ↗

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Source:arXiv Robotics — research abstracts · arxiv.org

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