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This is a Experimental Study study (also classified as: Cohort Study).

October 2, 2025Open Access

Implicit Kinodynamic Motion Retargeting for Human-to-humanoid Imitation Learning

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Proposed framework improves motion retargeting for humanoid robots, suggesting enhanced scalability and efficiency.

IKMR framework achieves efficient motion retargeting, enabling real-time scalability for humanoid robots across varied tasks.
The framework integrates motion topology representation and a dual encoder-decoder architecture for effective learning.
Extensive experiments validate the effectiveness of the proposed approach on humanoid robots in simulation and real-world settings.
The dynamics integration in IKMR allows for refining motion into physically feasible trajectories, enhancing controller training.

Chen et al. (2025) studied this question.

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October 2, 2025Open Access

View Full Paper

Ask AI

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Authors

Proposed framework improves motion retargeting for humanoid robots, suggesting enhanced scalability and efficiency.

IKMR framework achieves efficient motion retargeting, enabling real-time scalability for humanoid robots across varied tasks.
The framework integrates motion topology representation and a dual encoder-decoder architecture for effective learning.
Extensive experiments validate the effectiveness of the proposed approach on humanoid robots in simulation and real-world settings.
The dynamics integration in IKMR allows for refining motion into physically feasible trajectories, enhancing controller training.

Chen et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark