Unified Diffusion Transformer for Motion-Conditioned Robot Co-Design

The paper introduces Transformer Transformer, a unified diffusion transformer model that generates optimized robot designs conditioned on motion demonstrations. It employs RoboTokens for compact robot representation and Dynamics Self-Guidance for reward-agnostic motion optimization, achieving 73% lower tracking error in real-world tests.

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