2 papers
cs.RO2026
Towards Bridging the Gap between Large-Scale Pretraining and Efficient Finetuning for Humanoid Control
Weidong Huang, Zhehan Li, Hangxin Liu +3
Reinforcement learning (RL) is widely used for humanoid control, with on-policy methods such as Proximal Policy Optimization (PPO) enabling robust training via large-scale parallel…
cs.RO2026
ECO: Energy-Constrained Optimization with Reinforcement Learning for Humanoid Walking
Weidong Huang, Jingwen Zhang, Jiongye Li +6
Achieving stable and energy-efficient locomotion is essential for humanoid robots to operate continuously in real-world applications. Existing MPC and RL approaches often rely on e…