FGRL: Federated Growing Reinforcement Learning for Resilient Mapless Navigation in Unfamiliar Environments

FGRL: Federated Growing Reinforcement Learning for Resilient Mapless Navigation in Unfamiliar Environments

In this paper, we propose a federated growing reinforcement learning (FGRL) approach for solving the mapless navigation problem of unmanned ground vehicles (UGVs) facing cluttered unfamiliar obstacles. Deep reinforcement learning (DRL) has the potential to provide adaptive behaviors for autonomous a...

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Bibliographic Details
Main Authors: Shunyu Tian, Changyun Wei, Yajun Li, Ze Ji
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
collision avoidance
navigation
deep reinforcement learning
federated learning
Online Access:https://www.mdpi.com/2076-3417/14/23/11336
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