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HERO system enables humanoid robots to grasp objects with high precision

By PulseAugur Editorial · [1 sources] ·

Researchers have developed HERO, a modular system for humanoid robots to grasp objects in diverse real-world settings. This system combines large vision models for scene understanding with a novel residual-aware end-effector tracking policy for precise control. HERO achieved a 2.44cm end-effector tracking error, significantly outperforming previous methods, and demonstrated reliable grasping of everyday items in environments like offices and coffee shops. AI

IMPACT Enables more versatile and precise object interaction for humanoid robots in unstructured environments.

RANK_REASON The cluster contains a research paper detailing a new system for robotic control. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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

HERO system enables humanoid robots to grasp objects with high precision

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The cluster contains a research paper detailing a new system for robotic control. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Runpei Dong, Ziyan Li, Arjun Gupta, Xialin He, Saurabh Gupta ·

    HERO: Learning Humanoid End-Effector Control for Visual Whole-Body Open-Vocabulary Object Grasping

    arXiv:2602.16705v3 Announce Type: replace-cross Abstract: Visual loco-manipulation of arbitrary in-the-wild objects requires accurate end-effector (EE) control and a generalizable understanding of the scene from visual inputs (eg, RGB-D images). Existing imitation and sim2real me…

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