Geometry-Aware Humanoid Retargeting via Manifold ODEs
Overview
This paper introduces TaSP-KKT, a new method for interaction-preserving motion retargeting that transfers human demonstrations to humanoids while maintaining spatial relationships with objects and terrain. By modeling the continuous-time limit of frame-wise Karush-Kuhn-Tucker (KKT) conditions as an ordinary differential equation (ODE) on the robot configuration manifold, the approach connects existing temporally coupled constrained optimization methods to backward discretization of the ODE and proposes a forward discretization scheme. Numerical experiments indicate that TaSP-KKT achieves retargeting quality comparable to, though slightly lower than, OmniRetarget while running approximately twice as fast.
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- arXiv Robotics — research abstractsSignalGeometry-Aware Humanoid Retargeting via Manifold ODEs
This paper introduces TaSP-KKT, a new method for interaction-preserving motion retargeting that transfers human demonstrations to humanoids while maintaining spatial relationships with objects and terrain. By modeling the continuous-time limit of frame-wise Karush-Kuhn-Tucker (KKT) conditions as an ordinary differential equation (ODE) on the robot configuration manifold, the approach connects existing temporally coupled constrained optimization methods to backward discretization of the ODE and proposes a forward discretization scheme. Numerical experiments indicate that TaSP-KKT achieves retargeting quality comparable to, though slightly lower than, OmniRetarget while running approximately twice as fast.
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