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SMART system uses synthetic data for robotic articulated object manipulation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed SMART, a system designed to improve robotic manipulation of articulated objects through large-scale synthetic pretraining. The system utilizes SMART-Sim, a simulation platform with articulation-aware design, to generate over one million demonstrations across various tasks and objects. A vision-language-action model pretrained on this synthetic data demonstrates competitive performance on simulation benchmarks and achieves zero-shot sim-to-real transfer for real-world manipulation tasks. AI

IMPACT This research could significantly advance robotic manipulation capabilities by leveraging synthetic data for sim-to-real transfer.

RANK_REASON The cluster contains an academic paper detailing a new system and dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

SMART system uses synthetic data for robotic articulated object manipulation

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18 / 100
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The cluster contains an academic paper detailing a new system and dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, model release
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High
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jicong Ao, Shuhan Jiang, Yuling Zhong, Yanwen Liu, Yuhan Gao, Jiangyuan Zhao, Yang Zhang, Shiqiang Zhu, Chenjia Bai, Xuelong Li ·

    SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining

    arXiv:2610.07652v1 Announce Type: cross Abstract: The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations for these interactions remains challenging due to the precise contact and constra…

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