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A unified encoder architecture with no robot-specific parameters for distilling the behavior space to address all training embodiments simultaneously in less than a GPU-hour is proposed, demonstrating cross-embodiment generalization to morphologically similar robots.
ChronoSRL is introduced, which gives the critic's embeddings an explicit temporal geometry and predicts from their temporal embeddings not only the full distribution of goal-reaching times but also the time spent near the goal.
This work introduces an online embodiment adaptation framework for quadrupedal locomotion that infers embodiment parameters from short interaction histories and conditions control on the inferred hardware state to demonstrate the practicality of explicit online embodiment identification for rapid adaptation to joint-li...
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