Adaptive Environment Modeling Based Reinforcement Learning for Collision Avoidance in Complex Scenes
Shuaijun Wang,Rui Gao,Ruihua Han,Shengduo Chen,Chengyang Li,Qi Hao,Shuaijun Wang,Rui Gao,Ruihua Han,Shengduo Chen,Chengyang Li,Qi Hao
The major challenges of collision avoidance for robot navigation in crowded scenes lie in accurate environment modeling, fast perceptions, and trustworthy motion planning policies. This paper presents a novel adaptive environment model based collision avoidance reinforcement learning (i.e., AEMCARL) framework for an unmanned robot to achieve collision-free motions in challenging navigation scenari...
