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Research on Path Planning Based on Deep Reinforcement Learning

泰霖 周

Year
2025
Citations
1
Access
Open access

Abstract

随着自动化和智能系统的发展,高效的路径规划已成为机器人、自动驾驶汽车、无人机导航等领域的关键技术之一。本文主要研究基于深度强化学习的路径规划算法,我们设计了一系列奖励函数提高智能体路径规划能力,最后通过仿真实验验证算法有效性。With the development of automation and intelligent systems, efficient path planning has become one of the key technologies in the fields of robotics, autonomous vehicles, and drone navigation. In this paper, we study the path planning problem based on deep reinforcement learning. We design a series of reward functions to improve the agent’s path planning ability, and verify the effectiveness of the algorithm through simulation experiments.

Keywords

MathematicsReinforcement learningPath (computing)ReinforcementArtificial intelligenceComputer sciencePsychologySocial psychology

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