RopeDreamer uses quaternionic kinematic chains in a recurrent state space model with a dual decoder to cut open-loop prediction error by 40.52% over 50 steps on simulated DLO trajectories while preserving physical constraints.
Graph Neural Networks Exponen- tially Lose Expressive Power for Node Classification
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RopeDreamer: A Kinematic Recurrent State Space Model for Dynamics of Flexible Deformable Linear Objects
RopeDreamer uses quaternionic kinematic chains in a recurrent state space model with a dual decoder to cut open-loop prediction error by 40.52% over 50 steps on simulated DLO trajectories while preserving physical constraints.
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