Adaptive Deep Ant Colony Optimization–Asymmetric Strategy Network Twin Delayed Deep Deterministic Policy Gradient Algorithm: Path Planning for Mobile Robots in Dynamic Environments

Path planning is one of the main focal points and challenges in mobile robotics research. Traditional ant colony optimization (ACO) algorithms encounter issues such as low efficiency, slow convergence, and a tendency to become stuck in local optima and search stagnation when applied to complex dynam...

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Vydané v:	Electronics (Basel) Ročník 13; číslo 20; s. 4071
Hlavní autori:	Li, Xiangcheng, Ruan, Zhaokai, Ou, Yang, Ban, Dongri, Sun, Youming, Qin, Tuanfa, Cai, Yiyi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.10.2024
Predmet:	Adaptive algorithms Algorithms Ant colony optimization Asymmetry Changing environments Convergence Diffusion rate Distance learning Efficiency Heuristic Localization Optimization algorithms Optimization techniques Path planning Pheromones Planning Robotics Robots Strategy Unmanned aerial vehicles New York
ISSN:	2079-9292, 2079-9292
On-line prístup:	Získať plný text
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