Google has rolled out the RT-1 robot model, boasting features comparable to those of the GPT-based systems used in OpenAI.
The newly released RT-1 model by Google marks a pivotal moment in robotic capabilities, seamlessly integrating with Google's comprehensive robotics projects, including its autonomous vehicle technologies. It has been designed to handle a staggering array of over 700 different instructions, achieving a remarkable success rate of 97% in practical applications.
The recent breakthroughs in machine learning have greatly benefitted from a unified strategy that employs expansive and varied datasets coupled with intricate model frameworks. While various attempts have been made to adapt this approach for robotics, highly advanced models haven't been extensively utilized in this sector compared to others.
To build a system capable of adapting to a variety of tasks while demonstrating durability against functioning distractions, developers compiled a comprehensive dataset of robot trajectories. Over a span of 17 months, they collected 130,000 episodes using 13 advanced EDR robot manipulators, which feature articulated arms, grippers, and mobility. By employing remote teleoperation, human operators provided examples that were meticulously documented, detailing the commands executed by the robots. The dataset encompasses advanced skills such as handling items, managing drawers, orienting objects, and engaging with various tasks requiring dexterity.
Check out this video showcasing several PaLM-SayCan-RT1 extended task performances as they unfold in real-life kitchen scenarios.
Across all tested parameters, RT-1 exhibits a performance that significantly outstrips standard benchmarks, demonstrating outstanding levels of adaptability and strength.
The RT-1 Robotics Transformer stands out as a scalable model focused on generating action for practical robotics applications. By tokenizing both input and output data and leveraging a pre-trained EfficientNet with early language integration through a token learner, RT-1 has showcased impressive capabilities across a myriad of tasks, demonstrating extensive adaptability and resilience in real-world interactions.
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