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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Vydané v:	Journal of Robotics Ročník 2023; s. 1 - 11
Hlavní autori:	Zhang, HanBin, Shi, XianPeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Hindawi 05.04.2023 John Wiley & Sons, Inc Wiley
Predmet:	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
On-line prístup:	Získať plný text
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