1 citations · 3 across the 10 of their papers we have counts for
10 papers
ERFSL: An Efficient Reward Function Searcher via Language Models for Custom-Environment Multi-Objective Optimization (Student Abstract)
Guanwen Xie, Jingzehua Xu, Yiyuan Yang +2
We propose ERFSL, an efficient reward function searcher using large language models (LLMs) for custom-environment, multi-objective learning-based methods (LB). ERFSL generates rewa…
AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)
Yimian Ding, Jingzehua Xu, Yiyuan Yang +3
Ocean exploration places high demands on autonomous underwater vehicles, especially when there's observation delay. We propose age of information optimized Markov decision process…
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…
Never too Cocky to Cooperate: An FIM and RL-based USV-AUV Collaborative System for Underwater Tasks in Extreme Sea Conditions
Jingzehua Xu, Guanwen Xie, Jiwei Tang +5
This paper develops a novel unmanned surface vehicle (USV)-autonomous underwater vehicle (AUV) collaborative system designed to enhance underwater task performance in extreme sea c…
Never too Prim to Swim: An LLM-Enhanced RL-based Adaptive S-Surface Controller for AUVs under Extreme Sea Conditions
Guanwen Xie, Jingzehua Xu, Yimian Ding +3
The adaptivity and maneuvering capabilities of Autonomous Underwater Vehicles (AUVs) have drawn significant attention in oceanic research, due to the unpredictable disturbances and…
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…
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…
USV-AUV Collaboration Framework for Underwater Tasks under Extreme Sea Conditions
Jingzehua Xu, Guanwen Xie, Xinqi Wang +2
Autonomous underwater vehicles (AUVs) are valuable for ocean exploration due to their flexibility and ability to carry communication and detection units. Nevertheless, AUVs alone o…
Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement
Guanwen Xie, Jingzehua Xu, Yiyuan Yang +2
Achieving the effective design and improvement of reward functions in reinforcement learning (RL) tasks with complex custom environments and multiple requirements presents consider…
Enhancing Information Freshness: An AoI Optimized Markov Decision Process
Jingzehua Xu, Yimian Ding, Yiyuan Yang +2
Ocean exploration utilizing autonomous underwater vehicles (AUVs) via reinforcement learning (RL) has emerged as a significant research focus. However, underwater tasks have mostly…