研究人员开发了一个名为DIRECT的新框架，用于优化具身AI规划器的计算资源分配。该系统分析多模态场景上下文以智能地路由计算，与固定的模型选择策略相比，提高了效率并降低了延迟。在基准测试和物理机器人手臂上的实验表明，DIRECT可以以显著更低的成本实现相当或更好的成功率。 AI
影响 优化具身AI的资源分配，可能实现更高效、更具成本效益的机器人系统部署。
排序理由 该集群包含一篇详细介绍新框架和实验结果的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
完整方法见我们的编辑标准。
arXiv:2606.12402v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time compute to improve capability. However, we observe that doing so increases latency,…
Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time compute to improve capability. However, we observe that doing so increases latency, token usage, and FLOPs while yielding uneven, oft…