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English(EN) Steering Generative Robot Policies with Lexicographic Preferences

新方法使用优先目标引导生成式机器人策略

研究人员开发了一种新颖的方法,可以在推理时引导预训练的生成式机器人策略,使其在不改变策略权重的情况下遵循优先部署目标。该方法使用动态障碍物引导来确保在满足较低优先级目标的同时,不会增加较高优先级的成本。该方法在导航和操作基准测试中显示出更高的成功率和偏好合规性,优于现有基线,并在各种参数设置下表现出鲁棒性。 AI

影响 使机器人行为在实际部署中更具适应性和用户对齐性。

排序理由 该集群包含一篇详细介绍生成式机器人策略新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新方法使用优先目标引导生成式机器人策略

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该集群包含一篇详细介绍生成式机器人策略新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yixuan Jia, Jonathan P. How ·

    使用词典式偏好引导生成式机器人策略

    arXiv:2609.15014v1 Announce Type: cross Abstract: Pretrained generative robot policies can produce effective behaviors across diverse environments, but deployment can lead to requirements and preferences that may not have been represented during training. Furthermore, at deployme…