OceanGym: A Benchmark Environment for Underwater Embodied Agents

arXiv:2509.26536 · cs.CL, cs.AI, cs.CV, cs.LG, cs.RO · Submitted 2025-09-30 · Read on arXiv

cs.CL, cs.AI, cs.CV, cs.LG, cs.RO

Submitted: 2025-09-30

Updated: 2026-08-28

Code: https://github.com/OceanGPT/OceanGym

Project page: https://oceangpt.github.io/OceanGym

Terminology

• Benchmark — 29× in this paper · explained in 2 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Embodied AI — 7× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Fidelity — 5× in this paper · explained in 2 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Adaptability — 4× in this paper · explained in 1 episode
• Autonomous Underwater Vehicle — 4× in this paper
• Benchmarking — 4× in this paper · explained in 3 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Unreal Engine — 3× in this paper
• World Model — 3× in this paper · explained in 7 episodes
• AI Agents — 2× in this paper · explained in 2 episodes
• Elias — 2× in this paper · explained in 2 episodes
• Test-time Scaling — 2× in this paper · explained in 2 episodes
• AI Alignment — 1× in this paper · explained in 2 episodes
• Action Decoder — 1× in this paper · explained in 1 episode
• Agentic Problem — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• GPT-4 Technical Report
• Underwater Robotic Simulators Review for Autonomous System Development
• Qwen2.5-VL Technical Report
• FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models
• RoboGPT: an intelligent agent of making embodied long-term decisions for daily instruction tasks
• EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents
• MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Robotics
• RynnEC: Bringing MLLMs into Embodied World
• Understanding World or Predicting Future? A Comprehensive Survey of World Models
• EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models
• Embodied AI Agents: Modeling the World
• NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation
• Openfly: A comprehensive platform for aerial vision-language navigation
• BEDI: A Comprehensive Benchmark for Evaluating Embodied Agents on UAVs
• Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision
• Embodied Web Agents: Bridging Physical-Digital Realms for Integrated Agent Intelligence
• An Embodied Generalist Agent in 3D World
• VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
• AI2-THOR: An Interactive 3D Environment for Visual AI
• CityNav: A Large-Scale Dataset for Real-World Aerial Navigation

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