1 citations · 1 across the 5 of their papers we have counts for
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Multi-Objective-Optimization Assisted Data Collection Framework for IoUT Based on Offline Reinforcement
Yimian Ding, Xinqi Wang, Jingzehua Xu +3
The Information Updating Networks (IUNs) offers significant potential for ocean exploration but encounters challenges due to dynamic underwater environments and severe system atten…
Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks
Yimian Ding, Jingzehua Xu, Guanwen Xie +2
This study presents a novel environment-aware reinforcement learning (RL) framework designed to augment the operational capabilities of autonomous underwater vehicles (AUVs) in und…
When Motion Learns to Listen: Diffusion-Prior Lyapunov Actor-Critic Framework with LLM Guidance for Stable and Robust AUV Control in Underwater Tasks
Jingzehua Xu, Weiyi Liu, Weihang Zhang +4
Autonomous Underwater Vehicles (AUVs) are indispensable for marine exploration; yet, their control is hindered by nonlinear hydrodynamics, time-varying disturbances, and localizati…
EFILN: The Electric Field Inversion-Localization Network for High-Precision Underwater Positioning
Yimian Ding, Jingzehua Xu, Guanwen Xie +3
Accurate underwater target localization is essential for underwater exploration. To improve accuracy and efficiency in complex underwater environments, we propose the Electric Fiel…