LOCOMOTION
RAVEN：基于强化学习自适应可见图规划的鲁棒仿人导航与无碰撞MPC
Ruochen Hou, Shiqi Wang, Beom Jun Kim, Hanzhang Fang, Mehak Singal, Dennis W. Hong
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出RAVEN框架，通过强化学习自适应调整可见图规划器的几何参数，以补偿控制延迟和跟踪误差，实现鲁棒的仿人导航。结合无碰撞模型预测控制，该框架在动态环境中有效生成安全轨迹。
关键词
humanoid navigationreinforcement learningmodel predictive controlvisibility graphcollision avoidance
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