A dynamics-aware proprioceptive estimator recovers granular stiffness parameters consistently across hopping speeds by decomposing forces into inertia, gravity, and acceleration-dependent added-mass effects from grain entrainment.
Learning quadrupedal locomotion on deformable terrain
2 Pith papers cite this work. Polarity classification is still indexing.
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AttenNKF augments InEKF with an attention-based neural compensator trained in latent space to correct foot-slip errors in legged robot state estimation.
citing papers explorer
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From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media
A dynamics-aware proprioceptive estimator recovers granular stiffness parameters consistently across hopping speeds by decomposing forces into inertia, gravity, and acceleration-dependent added-mass effects from grain entrainment.
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Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation
AttenNKF augments InEKF with an attention-based neural compensator trained in latent space to correct foot-slip errors in legged robot state estimation.