A Novel Obstacle Traversal Method for Multiple Robotic Fish Based on Cross-Modal Variational Autoencoders and Imitation Learning

Precision control of multiple robotic fish visual navigation in complex underwater environments has long been a challenging issue in the field of underwater robotics. To address this problem, this paper proposes a multi-robot fish obstacle traversal technique based on the combination of cross-modal...

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Veröffentlicht in:	Biomimetics (Basel, Switzerland) Jg. 9; H. 4; S. 221
Hauptverfasser:	Wang, Ruilong, Wang, Ming, Zhao, Qianchuan, Gong, Yanling, Zuo, Lingchen, Zheng, Xuehan, Gao, He
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 01.04.2024
Schlagworte:	Algorithms CM-VAE Deep learning Design and construction Electronics in navigation Engineering research Fishes Image processing imitation learning Localization Machine learning Mapping Methods multiple robotic fish Navigation systems Neural networks Observational learning Robotics Robots, Industrial Sensors Sensory integration Underwater navigation Underwater robots visual navigation China CM-VAE imitation learning visual navigation multiple robotic fish
ISSN:	2313-7673, 2313-7673
Online-Zugang:	Volltext
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