Multi-Source Data-Driven Terrestrial Multi-Algorithm Fusion Path Planning Technology

Multi-Source Data-Driven Terrestrial Multi-Algorithm Fusion Path Planning Technology

This paper presents a multi-source data-driven hybrid path planning framework that integrates global A* search with local Deep Q-Network (DQN) optimization to address complex terrestrial routing challenges. By fusing ASTER GDEM terrain data with OpenStreetMap (OSM) road networks, we construct a stan...

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Bibliographic Details
Main Authors: Xiao Ji, Peng Liu, Meng Zhang, Chengchun Zhang, Shuang Yu, Bing Qi, Man Zhao
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
Subjects:
multi-source data
path planning algorithms
A* algorithm optimization
deep reinforcement learning
dynamic decision making
Online Access:https://www.mdpi.com/1424-8220/25/12/3595
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