Redesigned regularization addresses implementation gaps in policy smoothing for RL, yielding smoother motions with improved performance and robustness on a quadruped robot in sim-to-real settings.
Learning smooth time-varying linear policies with an action jacobian penalty,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Redesigning Regularization for Effective Policy Smoothing
Redesigned regularization addresses implementation gaps in policy smoothing for RL, yielding smoother motions with improved performance and robustness on a quadruped robot in sim-to-real settings.