Google's Gemini Robotics: Advanced AI for Independent Operation
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Today on AI News, Google has unleashed their latest creation, Gemini Robotics on Device, a groundbreaking AI model that equips robots with the ability to operate independently, without relying on cloud-based networks. This means robots can now tackle complex tasks with finesse, revolutionizing their applications in homes, factories, and unpredictable environments. Unlike traditional robotic models, Gemini Robotics on Device delivers general-purpose dexterity and rapid task adaptation right at the robot's fingertips, eliminating the need for remote servers. This cutting-edge model, building on Gemini 2.0, integrates vision, language, and action capabilities, allowing robots to understand complex environments, follow instructions, and manipulate various objects seamlessly.
Furthermore, Gemini Robotics on Device showcases exceptional generalization abilities, demonstrating superior performance in multi-step tasks that previously challenged conventional robotic models. The model's adaptability extends across different robotic platforms, showcasing its versatility and potential impact across various tasks and environments. Notably, Gemini Robotics on Device has outperformed other VLA models in challenging scenarios, displaying unmatched capabilities in adapting to new objects, scenes, and instructions. Additionally, the model supports user fine-tuning, ensuring efficiency and minimal computational resource requirements for seamless integration into standard robotic platforms.
In parallel, the introduction of LUV, a new framework for vision language whole-body control in humanoid robots, marks a significant milestone in AI android control. This innovative framework bridges the gap between semantic understanding and dynamic behaviors necessary for real-world tasks, offering a solution to the limitations of previous models. Through a two-tiered architecture inspired by cognitive science, LUV achieves remarkable success rates in closed-loop evaluations across a diverse range of scenarios. The integration of transformer-based vision language backbones and latent verb decoding enables precise and efficient whole-body motion control, setting a new standard in humanoid robotics.
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Image copyright Youtube
Image copyright Youtube
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