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RL-QPSO网:深度强化学习增强的QPSO,用于高效的移动机器人路径规划

Yang Jing1, Li Weiya1

  • 1Hebi Institute of Engineering and Technology, Henan Polytechnic University, Hebi, Henan, China.

Frontiers in neurorobotics
|January 23, 2025
PubMed
概括

一个新的RL-QPSO Net模型通过结合量子启发的粒子群优化和深度强化学习来增强移动机器人路径规划. 这种方法提高了复杂环境中的全球最佳性和实时适应性.

关键词:
量子行为粒子群集优化复杂的环境 复杂的环境深度强化学习的学习.移动机器人 移动机器人路径规划路径规划路径规划

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