A Hybrid Path Planning Framework Integrating Deep Reinforcement Learning and Variable-Direction Potential Fields

A Hybrid Path Planning Framework Integrating Deep Reinforcement Learning and Variable-Direction Potential Fields

To address the local optimality in path planning for logistics robots using APF (artificial potential field) and the stagnation problem when encountering trap obstacles, this paper proposes VDPF (variable-direction potential field) combined with RL (reinforcement learning) to effectively solve these...

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Bibliographic Details
Main Authors: Yunfei Bi, Xi Fang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Mathematics
Subjects:
path planning
reinforcement learning
artificial potential field
autonomous navigation
Online Access:https://www.mdpi.com/2227-7390/13/14/2312
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