Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint Generators
Linh Kästner,Xinlin Zhao,Teham Buiyan,Junhui Li,Zhengcheng Shen,Jens Lambrecht,Cornelius Marx,Linh Kästner,Xinlin Zhao,Teham Buiyan,Junhui Li,Zhengcheng Shen,Jens Lambrecht,Cornelius Marx
Deep Reinforcement Learning has emerged as an efficient dynamic obstacle avoidance method in highly dynamic environments. It has the potential to replace overly conservative or inefficient navigation approaches. However, integrating Deep Reinforcement Learning into existing navigation systems is still an open frontier due to the myopic nature of Deep-Reinforcement-Learning-based navigation, which ...
