Toward Intelligent Ocean Exploration: Artificial Intelligence-Driven Innovations in AUV Systems and Future Trends

The integration of artificial intelligence (AI) is revolutionizing intelligent ocean exploration, offering transformative solutions for next-generation autonomous underwater vehicles (AUVs). This paper systematically reviews current research on AUVs, identifying three critical challenges: limited underwater endurance due to energy constraints (limited battery capacity and inefficient recharge methods), insufficient adaptability of autonomous control systems in complex marine environments (dynamic obstacle avoidance, unpredictable current disturbances and poor algorithm generalization), and degraded visual perception caused by underwater turbidity and lighting variability (underwater turbidity, light reflection, illumination, mirrored targets, suspended particles, etc.). We analyze these technical bottlenecks through an AI-driven lens and propose targeted improvement strategies. Furthermore, emerging development trends are projected, emphasizing the synergistic advancement of four key areas: Wireless power transfer for AUVs, autonomous underwater vehicle–manipulator systems with artificial intelligence; advanced sensing, navigation and autonomy for AUVs; and collaborative operations (underwater robot swarm operations). The analysis highlights how these innovations will enable adaptive, energy-efficient and environmentally resilient AUV systems, ultimately accelerating sustainable ocean exploration and resource utilization.

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Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2025-06-16
DOI
https://doi.org/10.1142/s0129156425406369
Citations
1
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
1.15
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article

Toward Intelligent Ocean Exploration: Artificial Intelligence-Driven Innovations in AUV Systems and Future Trends

Chee-Loon Siow, Jianjun Song
1 citations
International Journal of High Speed Electronics and Systems
Maritime Navigation and Safety
1.15
article

Toward Intelligent Ocean Exploration: Artificial Intelligence-Driven Innovations in AUV Systems and Future Trends

Chee-Loon Siow, Jianjun Song
article en
1 citations

Abstract

The integration of artificial intelligence (AI) is revolutionizing intelligent ocean exploration, offering transformative solutions for next-generation autonomous underwater vehicles (AUVs). This paper systematically reviews current research on AUVs, identifying three critical challenges: limited underwater endurance due to energy constraints (limited battery capacity and inefficient recharge methods), insufficient adaptability of autonomous control systems in complex marine environments (dynamic obstacle avoidance, unpredictable current disturbances and poor algorithm generalization), and degraded visual perception caused by underwater turbidity and lighting variability (underwater turbidity, light reflection, illumination, mirrored targets, suspended particles, etc.). We analyze these technical bottlenecks through an AI-driven lens and propose targeted improvement strategies. Furthermore, emerging development trends are projected, emphasizing the synergistic advancement of four key areas: Wireless power transfer for AUVs, autonomous underwater vehicle–manipulator systems with artificial intelligence; advanced sensing, navigation and autonomy for AUVs; and collaborative operations (underwater robot swarm operations). The analysis highlights how these innovations will enable adaptive, energy-efficient and environmentally resilient AUV systems, ultimately accelerating sustainable ocean exploration and resource utilization.

International Journal of High Speed Electronics and SystemsVol. 35(04)
Shanghai Technical Institute of Electronics & Information (CN), University of Technology Malaysia (MY)
Openalex Percentile: Top 22%
Maritime Navigation and Safety
1.15
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Toward Intelligent Ocean Exploration: Artificial Intelligence-Driven Innovations in AUV Systems and Future Trends — Chee-Loon Siow, Jianjun Song · International Journal of High Speed Electronics and Systems (2025) | TGRS Research Map | TGRS