Design a path – planning strategy for mobile robot in multi-structured environment based on distributional reinforcement learning

Design a path – planning strategy for mobile robot in multi-structured environment based on distributional reinforcement learning

The article proposes a novel path-planning strategy for mobile robots moving in unknown environments by integrating Lightweight Learned Image Denoising with Instance Adaptation (LIDIA) and Quantile Regression Deep Q-Network (QR-DQN) within a unified framework. This combination approach aims to allow...

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Bibliographic Details
Main Authors: Anh-Tu Nguyen, Duc-Duy Pham, Van-Nghia Le, Vu-Hai Luu
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:MethodsX
Subjects:
Mobile robot
Path – planning
Distributional reinforcement learning
QR – DQN Network
Sub – reward mechanism
Online Access:http://www.sciencedirect.com/science/article/pii/S221501612500398X
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