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RT-1: Robotics Transformer for Real-World Control at Scale

RT-1: Robotics Transformer for Real-World Control at Scale

Section titled “RT-1: Robotics Transformer for Real-World Control at Scale”

⚠️ AI 生成 · 建议对照原文 本页为自动整理的学习笔记;关键数据与引用如需引用,请回查 PDF / 官方版本。

学习档位 自动卡

类型 文献 · 更新 2026-07-19

所属 具身智能体 · VLA 模型

  • topic: embodied-agents
  • sources: openalex
  • retrieved_at: 2026-07-20
  • query: embodied AI agents foundation models
  • doi: 10.15607/rss.2023.xix.025
  • score_total: 53
  • suggested_tier: recent

(no prose relevance explanation — numeric score only or HTTP source)

(no snippet evidence in candidate pool)

AI analysis (heuristic fallback, needs-source-verification)

Section titled “AI analysis (heuristic fallback, needs-source-verification)”

Status: metadata_only · Source: metadata

Metadata-only card for RT-1: Robotics Transformer for Real-World Control at Scale.

生成:2026-07-21 · 来源条数 0 · 模型 heuristic · 需人工核验数字

围绕「RT-1: Robotics Transformer for Real-World Control at Scale」的核心问题与动机(待结合全文核验)。

  • 见原文方法章节;以下为基于摘要/摘录的要点提示。
  • 本地摘录暂缺。

与相近工作的关系待核验;请对照 related work。

  • 勿仅凭摘要推断未给出的数值指标。
  1. 这篇工作的输入/输出表示是什么?(RT-1: Robotics Transformer for Real-World Control at Scale)
  2. 训练目标与评测协议各是什么?
  3. 主要失败模式或局限是什么?
  • (本次未抓取到白名单二次解读页)
flowchart LR
A["输入 / 观测"] --> B["表示 / 编码"]
B --> C["推理 / 解码"]
C --> D["输出 / 动作或检测"]
%% method sketch for: RT-1: Robotics Transformer for Real-World Control at Scale

方法结构示意(重绘;细节以原论文为准,待 PDF 核验)。

展开英文 Paper Card / AI deep analysis
Field Content
Year 2023
Authors Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter
arXiv
DOI 10.15607/rss.2023.xix.025
Topics embodied-agents, embodied-foundation-models, vla-models
展开 Extract / Selections / Local assets
  • embodied-agents: tier=watch rank=5 score=53 — auto refresh 2026-07-19 sources=openalex
  • embodied-foundation-models: tier=foundational rank=2 score=58 — RT-1 is the large-scale robotics transformer predecessor to RT-2/OpenVLA
  • vla-models: tier=foundational rank=1 score=85 — RSS 2023 RT-1 — robotics transformer for real-world control at scale
(no PDF text available; metadata-only card)