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Google DeepMind releases Gemini Robotics 2, giving humanoid robots whole-body AI control

Google DeepMind launched Gemini Robotics 2 on July 30, a new family of AI models that enables humanoid and other robots to coordinate full-body movement, perform fine manipulation tasks, and collaborate with multiple robots simultaneously; a demonstration with Apptronik's humanoid showed the system screwing in a light bulb with 92% success, and picking up a watering can and clearing trash

الذكاء الاصطناعي· active اللعبة الطويلة·ما الذي تعطّل ·6 قراءات · ·تحديث rbtfl 31 يوليو 2026
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انقسام التغطية

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United States

Engadget

“Google's new Gemini Robotics 2 platform allows for 'intelligent whole-body control' as demonstrated in videos of bots cleaning trash and picking up watering cans.”

US tech consumer publication, demonstration and practical capability angleاقرأ النص الأصلي ↗

United States

SiliconANGLE

“Google DeepMind debuts Gemini Robotics 2 model series for humanoid robots.”

Enterprise and AI technology trade publication, model-series architectureاقرأ النص الأصلي ↗

United States

The AI Insider

“Google DeepMind introduced Gemini Robotics 2, a family of AI models designed to give robots whole-body control, finer manipulation and the ability to work together on complex tasks.”

AI-focused newsletter, whole-body coordination architecture and multi-robot capabilityاقرأ النص الأصلي ↗

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Summary

Google Deepmind released Gemini Robotics 2 on July 30, a family of AI models designed to give humanoid and other robots whole-body coordination, fine-grained manipulation, and the ability to coordinate tasks across multiple robots. The system was demonstrated with Apptronik's humanoid robot performing tasks including unscrewing a light bulb (92% success rate), clearing trash, and picking up objects. Gemini Robotics 2 differs from earlier robotics AI by simultaneously controlling head, torso, arms, and legs rather than treating each limb independently. Google said the model series targets a range of robot form factors.

Why it matters

Whole-body coordination is the main unsolved bottleneck in humanoid robotics: robots that cannot balance and manipulate at the same time fail on tasks that require both. A 92% success rate on a screw-in task with simultaneous whole-body movement, if reproducible outside a lab, represents a practical advance. Google DeepMind is competing with Tesla (Optimus), Figure, Boston Dynamics, and Agility Robotics for leadership in the humanoid AI stack, and a robotics-focused Gemini model family signals Alphabet treating robotics as a product line rather than a research project.

What to watch

  • Whether Gemini Robotics 2 is made available to third-party robot manufacturers beyond Apptronik, and on what commercial terms
  • Competing releases from Tesla, Figure, and Boston Dynamics, all of which have announced comparable whole-body coordination projects for 2026
  • China's parallel push, with Beijing's robot export restriction rules from July 30 signalling intent to control the robotics supply chain

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