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DONIC tracker learns generalist bimanual control from human demonstrations · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed DONIC, a novel generalist bimanual tracker capable of controlling two robot hands to replicate human demonstrations. Trained using reinforcement learning with recycled successful executions and per-hand rewards, DONIC demonstrates high success rates on unseen objects and trajectories without requiring fine-tuning. The system was trained on BiHOI, a new dataset comprising 1,575 bimanual interaction sequences across 229 objects, which emphasizes sustained two-hand contact. AI

IMPACT This research advances bimanual robotic manipulation, potentially enabling more complex and human-like interactions in robotics.

RANK_REASON The cluster describes a new research paper detailing a novel AI model and dataset.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

DONIC tracker learns generalist bimanual control from human demonstrations · 2 sources tracked

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COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    DONIC: Generalist Dexterous Bimanual Tracking Control from Human Demonstrations

    DONIC is a generalist bimanual tracker trained on diverse human-motion data that uses reinforcement learning with recycled demonstrations and per-hand rewards to achieve high success on unseen objects without fine-tuning.

  2. arXiv cs.CV TIER_1 English(EN) · Mingze Sun, Ziang Cao, Yuan Fei, Qiankuan Tao, Zihan Wang, Tianqi Liu, Junhao Chen, Haiwen Diao, Fangzhou Hong, Zhaoxi Chen, Ziwei Liu ·

    DONIC: Generalist Dexterous Bimanual Tracking Control from Human Demonstrations

    arXiv:2610.29997v1 Announce Type: cross Abstract: Despite recent progress in dexterous reference tracking, existing models focus primarily on single-hand manipulation and a limited range of interactions, leaving the bimanual dexterous behaviors common in real life unaddressed. Th…

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