Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning
Kyowoon Lee,Seongun Kim,Jaesik Choi,Kyowoon Lee,Seongun Kim,Jaesik Choi
For robotic vehicles to navigate robustly and safely in unseen environments, it is crucial to decide the most suitable navigation policy. However, most existing deep reinforcement learning based navigation policies are trained with a hand-engineered curriculum and reward function which are difficult to be deployed in a wide range of real-world scenarios. In this paper, we propose a framework to le...
