Proprioceptive distribution matching adapts simulators for legged robot policies by comparing observation and action distributions, reducing sim-to-real gaps with minimal real data and no external sensing.
Residual physics learning and system identification for sim-to-real transfer of policies on buoyancy assisted legged robots,
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Simulator Adaptation for Sim-to-Real Learning of Legged Locomotion via Proprioceptive Distribution Matching
Proprioceptive distribution matching adapts simulators for legged robot policies by comparing observation and action distributions, reducing sim-to-real gaps with minimal real data and no external sensing.