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Teamwork makes the dream work. To test multi-robot collaboration with Gemini Robotics 2, we challenged our Apollo and Duo robots to tidy up a messy garage. The high-level reasoning model breaks down what to do, where to go, and identifies the exact moment to hand over control ↓

Google DeepMind

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For decades, we’ve dreamed of robots that can seamlessly step into our world and lend a hand. Today, we take a major stride toward making that dream a reality: Introducing Gemini Robotics 2 from Google DeepMind, the intelligence layer powering the next generation of truly adaptable robots. This major advance unlocks intelligent whole-body control, advanced dexterity, and even multi-robot collaboration 🤯. Ok but... how does a robot actually "think"? Real-world tasks take time and planning. To manage that complexity, our new embodied reasoning model, Gemini Robotics ER 2, acts as the robot’s high-level brain, enhancing the robot’s capabilities to: — Observe the environment — Reason about the actions needed to complete the task — Coordinate with the vision-language-action model to carry out actions — Track progress until the job is done This setup allows robots to execute complex multi-step workflows, self-correct if a step fails, and adapt to completely novel situations. Learn more about Gemini Robotics ER 2 (and our two other brand new models) here:

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Control a robot in simulation with the Gemini Robotics Embodied Reasoning model 🤖 Direct tasks like object localization and placement by simply prompting a robotic arm to pick up and place objects.

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We took a robot to RSS in LA running our new Gemini Robotics On-Device VLA model. People interacted with the model with new objects and instructions in a brand new environment and the results were amazing!

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Vision-language models can control robots, but what if the prompt is too complex for the robot to follow directly? We developed a way to get robots to “think through” complex instructions, feedback, and interjections. We call it the Hierarchical Interactive Robot (Hi Robot).

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John: "Over in China, they’re doing robot Olympics. They’re doing marathons and all sorts of stuff." Figure founder Brett Adcock: “We look at the distribution of what humans do that is useful, and we [designed our humanoid] to do as much of that as possible.” “These things where we run marathons, or we do backflips, or we do karate moves—they’re not in the main part of the distribution. They don’t matter. And if you really want to size for those, you’re going to build a really expensive and unsafe robot that’s hard to manufacture.” “People want the $10,000 humanoid that can do general-purpose work. We want it to do laundry and dishes and be a companion. I want to ship robots at scale into the workforce to do logistics and healthcare, and build buildings and data centers.” "I don't need [our humanoid] to do backflips to do any of that work. I want robots building other robots."

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🤖 The robots have arrived. Now, we bring them to life with Robotics OS, the first end-to-end decentralized stack. Each robot will receive an on-chain machine identity within the Edge Network, joining the decentralized future of robotics. A new era where robots run on $EDGE.

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