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English(EN) GreenWAM: A World Foundation Model for Robotics

GreenWAM:一个用于机器人控制和预测的统一基石模型

研究人员推出 GreenWAM,一个专为机器人设计的全新世界基石模型。该单一模型既是动作条件的世界模型,也是策略,能够跨越包括双臂机器人和人形机器人等 20 个不同的机器人家族运行。GreenWAM 在 WorldArena 1.0 的世界预测任务上表现出色,超越了现有模型,并且在 RoboTwin 2.0 等排行榜以及 LIBERO-Plus、CALVIN 和 LIBERO 等基准测试中作为策略也取得了有竞争力的结果。该模型还成功应用于一台真实的人形机器人以进行实时控制。 AI

影响 这种统一的模型方法可以通过为不同类型的机器人提供一个用于世界预测和动作控制的单一系统,从而简化机器人开发。

排序理由 该条目描述了一篇介绍机器人领域新型基石模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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GreenWAM:一个用于机器人控制和预测的统一基石模型

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该条目描述了一篇介绍机器人领域新型基石模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    GreenWAM:机器人领域的全球基础模型

    A robot needs a world model that predicts how its actions will change the scene and a policy that chooses those actions. Models are usually built and evaluated for only one of these roles, and every robot records its actions in its own format. We ask whether one robot world model…