Efficient Deep Reinforcement Learning for Optimal Path Planning

Efficient Deep Reinforcement Learning for Optimal Path Planning

In this paper, we propose a novel deep reinforcement learning (DRL) method for optimal path planning for mobile robots using dynamic programming (DP)-based data collection. The proposed method can overcome the slow learning process and improve training data quality inherently in DRL algorithms. The...

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Bibliographic Details
Main Authors: Jing Ren, Xishi Huang, Raymond N. Huang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Electronics
Subjects:
deep reinforcement learning
global optimal path planning
dynamic programming
mobile robots
shortest path
continuous state space
Online Access:https://www.mdpi.com/2079-9292/11/21/3628

Internet

https://www.mdpi.com/2079-9292/11/21/3628

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