English(EN) OceanGym: A Benchmark Environment for Underwater Embodied Agents

OceanGym基准发布，用于水下AI智能体

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-31 04:00

研究人员推出了OceanGym，一个新颖的基准环境，旨在测试和提升水下具身智能体的AI能力。该平台通过引入八个真实的任务场景和由多模态大语言模型（MLLMs）驱动的统一智能体框架，解决了水下领域特有的挑战，如能见度低和水流动态变化。初步实验表明，当前MLLM驱动的智能体在感知、规划和适应性方面与人类专家存在显著的性能差距，凸显了该领域进一步发展的必要性。 AI

影响为具身AI建立了一个新的测试平台，可能加速现实世界水下机器人的开发。

排序理由该集群描述了一个新的AI研究基准环境的发布。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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Newsworthiness bucket: Tool; 该集群描述了一个新的AI研究基准环境的发布。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Yida Xue, Mingjun Mao, Xiangyuan Ru, Yuqi Zhu, Baochang Ren, Shuofei Qiao, Mengru Wang, Shumin Deng, Xinyu An, Ningyu Zhang, Ying Chen, Huajun Chen · 2026-08-31 04:00

OceanGym：面向水下具身智能体的基准环境

arXiv:2509.26536v3 Announce Type: replace Abstract: We introduce OceanGym, the first comprehensive benchmark for ocean underwater embodied agents, designed to advance AI in one of the most demanding real-world environments. Unlike terrestrial or aerial domains, underwater setting…

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报道来源 [1]

OceanGym：面向水下具身智能体的基准环境

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