ReActor jointly optimizes motion retargeting and RL policy training with an approximate gradient to generate physically consistent robot motions from human references using only sparse body correspondences.
arXiv preprint arXiv:2507.09371 (2025)
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.RO 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
CWI decouples MoCap data for upper-body manipulation and lower-body locomotion, using dual discriminators and multi-critic training plus distillation to produce a policy that works from hand poses and velocity commands alone.
ConTrack introduces a constrained RL method with online dual-variable adaptation and adaptive resets for improved long-horizon hand tracking in simulation and on real robots.
citing papers explorer
-
ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting
ReActor jointly optimizes motion retargeting and RL policy training with an approximate gradient to generate physically consistent robot motions from human references using only sparse body correspondences.
-
CWI: Composite Humanoid Whole-Body Imitation System for Loco-manipulation
CWI decouples MoCap data for upper-body manipulation and lower-body locomotion, using dual discriminators and multi-critic training plus distillation to produce a policy that works from hand poses and velocity commands alone.
-
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
ConTrack introduces a constrained RL method with online dual-variable adaptation and adaptive resets for improved long-horizon hand tracking in simulation and on real robots.