2 papers
cs.RO2025
Discovery of skill switching criteria for learning agile quadruped locomotion
Wanming Yu, Fernando Acero, Vassil Atanassov +4
This paper develops a hierarchical learning and optimization framework that can learn and achieve well-coordinated multi-skill locomotion. The learned multi-skill policy can switch…
cs.RO2018
Emergence of Human-comparable Balancing Behaviors by Deep Reinforcement Learning
Chuanyu Yang, Taku Komura, Zhibin Li
This paper presents a hierarchical framework based on deep reinforcement learning that learns a diversity of policies for humanoid balance control. Conventional zero moment point b…