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Explore advanced robotics modeling techniques in this 30-minute tutorial that delves into the challenges and solutions for training AI models to control robots. Begin with a comprehensive review of robotics AI models before examining the key challenges in robot modeling, including real-time processing requirements, system delays, and the complex multi-modality problem in robotics applications. Master the Action Chunking Transformer (ACT) model architecture and discover its variations including Bi-ACT for torque-based control and Multi-ACT for multi-task scenarios. Investigate cutting-edge approaches through detailed analysis of GR00T N1 and pi0 models, learning how GR00T leverages unlabeled data for training and understanding the comparative advantages of different modeling approaches. Gain practical insights into selecting appropriate robotics models for specific applications and explore advanced techniques that extend beyond traditional ACT and GR00T frameworks, with access to implementation scripts and resources for hands-on experimentation.
