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TaSP-KKT: Manifold ODE Accelerates Humanoid Motion Retargeting

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Pengyu Zhu and other authors propose TaSP-KKT, which models the continuous-time limit of OmniRetarget's per-frame KKT conditions as an ODE on the robot configuration manifold, and implements motion retargeting with forward discretization. The method requires only one weighted tangent-cone projection and a closed-form manifold update per step, avoiding repeated inner-loop SQP iterations. The authors state that in numerical experiments, TaSP-KKT's retargeting quality is comparable to but slightly lower than OmniRetarget, while running approximately twice as fast.

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  1. TaSP-KKT: Geometry-Aware Humanoid Motion Retargeting Based on Manifold ODEs

    The study proposes TaSP-KKT, which models the continuous-time limit of OmniRetarget's per-frame KKT conditions as an ODE on the robot configuration manifold and implements motion retargeting through forward discretization. The method requires only one weighted tangent-cone projection and a closed-form manifold update per step, avoiding repeated inner SQP iterations. In numerical experiments, retargeting quality is comparable to OmniRetarget but slightly lower, while running speed is about twice as fast.

    arXiv cs.RO ·

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Robot models and learningData and simulationResearch papers

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