Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics

Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics

We propose a deep reinforcement learning approach for solving a mapless navigation problem in warehouse scenarios. In our approach, an automatic guided vehicle is equipped with two LiDAR sensors and one frontal RGB camera and learns to perform a targeted navigation task. The challenges reside in the...

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Bibliographic Details
Main Authors: Honghu Xue, Benedikt Hein, Mohamed Bakr, Georg Schildbach, Bengt Abel, Elmar Rueckert
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Applied Sciences
Subjects:
deep reinforcement learning
automatic curriculum learning
autonomous navigation
multi-modal sensor perception
Online Access:https://www.mdpi.com/2076-3417/12/6/3153

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