フローベース生成モデルを利用したオフライン強化学習による動的環境下での移動ロボットナビゲーション

抄録

We propose a novel navigation method applying an offline reinforcement learning method based on Implicit Policy Constraint to mobile robot navigation in environments with pedestrians. The proposed method utilizes a flow-based generative model for the behavior policy, and the latent policy is trained using a method based on Advantage-Weighted Regression. The proposed method is evaluated in a simulation environment.