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arXiv · 2603.13825

Building Explicit World Model for Zero-Shot Open-World Object Manipulation

Xiaotong Li·Gang Chen·Javier Alonso-Mora
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Abstract

Open-world object manipulation remains a fundamental challenge in robotics. While Vision-Language-Action (VLA) models have demonstrated promising results, they rely heavily on large-scale robot action demonstrations, which are costly to collect and can hinder out-of-distribution generalization. In this paper, we propose an explicit-world-model-based framework for open-world manipulation that achieves zero-shot generalization by constructing a physically grounded digital twin of the environment. The framework integrates open-set perception, digital-twin reconstruction, sampling and evaluation of interaction strategies. By constructing a digital twin of the environment, our approach efficiently explores and evaluates manipulation strategies in physic-enabled simulator and reliably deploys the chosen strategy to the real world. Experimentally, the proposed framework is able to perform multiple open-set manipulation tasks without any task-specific action demonstrations, proving strong zero-shot generalization on both the task and object levels. Project Page: https://bojack-bj.github.io/projects/thesis/

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Xiaotong Li, Gang Chen, Javier Alonso-Mora. 2026-03-14. Building Explicit World Model for Zero-Shot Open-World Object Manipulation. https://arxiv.org/abs/2603.13825

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