A two-level reinforcement learning system that first learns animal-like gaits from flat-ground motion data, then learns small joint corrections that let a quadruped robot traverse rough terrain and navigate to goals.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Motion Priors Reimagined: Adapting Flat-Terrain Skills for Complex Quadruped Mobility
A two-level reinforcement learning system that first learns animal-like gaits from flat-ground motion data, then learns small joint corrections that let a quadruped robot traverse rough terrain and navigate to goals.