Biped robots with passive springs learn high-performance locomotion more efficiently via model-based RL by exploiting natural limit cycles from dynamic body-ground interactions.
Learning to walk with deep reinforcement learning: Forward dynamic simulation of a physics-based muscu- loskeletal model of an osseointegrated transfemoral amputee
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
-
Model-Based Reinforcement Learning Exploits Passive Body Dynamics for High-Performance Biped Robot Locomotion
Biped robots with passive springs learn high-performance locomotion more efficiently via model-based RL by exploiting natural limit cycles from dynamic body-ground interactions.