An Improved Quantum-Behaved Particle Swarm Optimization Algorithm Combined with Reinforcement Learning for AUV Path Planning

In order to solve the problem of fast path planning and effective obstacle avoidance for autonomous underwater vehicles (AUVs) in two-dimensional underwater environment, a path planning algorithm based on deep Q-network and Quantum particle swarm optimization (DQN-QPSO) was proposed. Five actions ar...

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Veröffentlicht in:	Journal of Robotics Jg. 2023; S. 1 - 11
Hauptverfasser:	Zhang, HanBin, Shi, XianPeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Hindawi 05.04.2023 John Wiley & Sons, Inc Wiley
Schlagworte:	Algorithms Artificial intelligence Autonomous underwater vehicles Design Energy consumption Machine learning Mathematical optimization Neural networks Obstacle avoidance Ocean currents Optimization Particle swarm optimization Path planning Planning Random variables Remote submersibles Simulation Vortices
ISSN:	1687-9600, 1687-9619
Online-Zugang:	Volltext
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