{
  "schema_version": 3,
  "paper": {
    "title": "GPT 6 Astra as an Embodied Policy",
    "kind": "research",
    "primary_source_ids": [
      "report",
      "code"
    ],
    "format": "web technical report; not a verified arXiv paper",
    "authors": [
      "Jiayi Su",
      "Yixin Zheng",
      "Mi Yan",
      "Li Yi",
      "Zhizheng Zhang",
      "He Wang"
    ],
    "arxiv": {
      "verified": false,
      "date_prefix_used": false,
      "reason": "No verified arXiv entry or v1 date; title preserved without invented date."
    }
  },
  "artifacts": {
    "article": "content/_posts/092-astra-embodied-policy.md",
    "deck": "lib/decks/astra-embodied-policy.html",
    "embed_src": "/lib/decks/astra-embodied-policy.html",
    "cover": "content/generated-covers/092-astra-embodied-policy.webp",
    "cover_source": "lib/papers/astra-embodied-policy/cover.svg",
    "verifier": "lib/papers/astra-embodied-policy/verify_metrics.py",
    "metric_subset": "lib/papers/astra-embodied-policy/selected-results.json"
  },
  "sources": [
    {
      "id": "report",
      "kind": "paper",
      "title": "GPT 6 Astra as an Embodied Policy — original web technical report",
      "url": "https://anonymous-report-421.github.io/public-website/index.html?lang=en&view=1",
      "revision": "6ead090465d3b0fb19e90eb70569689c19f73d00",
      "used_for": [
        "problem",
        "method",
        "results",
        "behavior analyses",
        "limitations",
        "all visual inventory"
      ]
    },
    {
      "id": "code",
      "kind": "code",
      "title": "GPT-as-Policy — official fixed integration and report source",
      "url": "https://github.com/anonymous-report-421/GPT-as-Policy/tree/8f3d362b077d8efb77e2a7274d5b2c20e2243846",
      "revision": "8f3d362b077d8efb77e2a7274d5b2c20e2243846",
      "used_for": [
        "action loop",
        "gate",
        "visibility",
        "native benchmark integration",
        "license scope",
        "model runtime",
        "protocol"
      ]
    },
    {
      "id": "results",
      "kind": "dataset",
      "title": "Public RoboDojo selected evaluation summaries",
      "url": "https://github.com/anonymous-report-421/GPT-as-Policy/blob/8f3d362b077d8efb77e2a7274d5b2c20e2243846/public_results/data.json",
      "revision": "8f3d362b077d8efb77e2a7274d5b2c20e2243846",
      "used_for": [
        "real case",
        "raw aggregation",
        "missing terminal outcomes",
        "steps and token arithmetic"
      ]
    },
    {
      "id": "robolab",
      "kind": "dataset",
      "title": "RoboLab selected final slots and historical baseline selection",
      "url": "https://github.com/anonymous-report-421/GPT-as-Policy/blob/8f3d362b077d8efb77e2a7274d5b2c20e2243846/report_web/robolab.json",
      "revision": "8f3d362b077d8efb77e2a7274d5b2c20e2243846",
      "used_for": [
        "49/50 vs 46/50",
        "retries",
        "historical baseline conditions",
        "decision-limit changes"
      ]
    },
    {
      "id": "native",
      "kind": "checker",
      "title": "RoboDojo — independent upstream task and native success/reward checker",
      "url": "https://github.com/robodojo-benchmark/RoboDojo/tree/ee67a1468510da7624a089164402359f2afc72c8",
      "revision": "ee67a1468510da7624a089164402359f2afc72c8",
      "used_for": [
        "instruction construction",
        "exact basket geometry",
        "home tolerances",
        "10/40/100 score stages",
        "checker blind spots"
      ]
    },
    {
      "id": "pi05",
      "kind": "web",
      "title": "π0.5 model introduction",
      "url": "https://www.pi.website/blog/pi05",
      "revision": "public page checked 2026-10-18",
      "used_for": [
        "VLA background only; reported checkpoint from code SOURCE.json"
      ]
    },
    {
      "id": "editorial",
      "kind": "web",
      "title": "Zhixiong — Astra embodied policy explainer (presentation reference only)",
      "url": "https://rookiexiong7.github.io/blog/posts/astra-embodied-policy/",
      "revision": "read 2026-10-18 after primary report and code",
      "used_for": [
        "section pacing",
        "figure placement",
        "audience bridging; not factual support"
      ]
    }
  ],
  "paper_reading": {
    "main_agent_complete_read": true,
    "appendices_included": true,
    "extracted_text_reviewed": true,
    "rendered_pages_reviewed": true,
    "page_count": 44,
    "rendered_page_ranges": [
      {
        "start": 1,
        "end": 44
      }
    ],
    "source_visuals_expected": 38,
    "visual_inventory_complete": true,
    "document_type": "Local browser print of fully expanded web report; NOT author-issued 44-page PDF.",
    "local_reading_artifacts": {
      "web_text": "tmp/astra-embodied-policy/report-en.md",
      "browser_print": "tmp/astra-embodied-policy/report-web-print.pdf",
      "rendered": "tmp/astra-embodied-policy/rendered/page-01.jpg ... page-44.jpg"
    },
    "included": "Abstract, all numbered report sections, folded skill/tool/controller explanations, behavioral analysis, citations, both metric toggles and RoboLab supplement; original videos inventoried but not all replayed.",
    "visual_inventory_scope": "4 numbered Figures, 3 numbered Tables, 21 numbered behavior videos, 10 task-initial-state illustrations. Additional unnumbered gallery clips/historical featured clip excluded from report inventory; linked gallery contains them.",
    "primary_code_read": "Both Dojo clients, gate, observations/session, prompt contexts, FK/IK, native task/reward code, RoboLab selection, licensing. No model API, robot, training or simulator experiments performed."
  },
  "note_sections": [
    {
      "role": "problem",
      "locator": "1. Motivation：看懂任务以后，还要把动作做出来"
    },
    {
      "role": "related-work",
      "locator": "2. Related Work：比较的是运行时分工，没有新的训练算法"
    },
    {
      "role": "method",
      "locator": "3. Method：候选、审查、短段执行，再重新观察"
    },
    {
      "role": "experiments",
      "locator": "4. Experiments：RoboDojo 有收益，RoboLab 给出相反结果"
    },
    {
      "role": "future-work",
      "locator": "5. Discussion：更值得检验的是候选如何帮到下一步"
    },
    {
      "role": "summary",
      "locator": "6. Conclusion：配合有价值，前提与代价不能省略"
    }
  ],
  "terminology": [
    {
      "term": "Direct / Hybrid",
      "kind": "actor",
      "source_ids": [
        "report"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "Abstract; §2.1"
        }
      ],
      "article_quote": "这份报告把 GPT 6 Astra 放进模拟机器人：每次看图、读取机械臂状态，再通过工具让机器人移动。作者比较两种用法：Astra 自己构造所有动作（Direct）；先让已有的机器人动作模型 π0.5 提出一段动作，再由 Astra 决定接受还是纠正（Hybrid）。研究问题是，理解目标和掌握操作技巧这两类能力，怎样配合才有用。"
    },
    {
      "term": "policy / VLA",
      "kind": "operation",
      "source_ids": [
        "report",
        "pi05"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "§2.1 and task-control documentation"
        }
      ],
      "article_quote": "机器人策略（policy）把当前观察变成下一段动作。能同时读图、读指令并输出机器人动作的模型通常称为 <a id=\"read-vla\" href=\"#basis-vla\">VLA（Vision-Language-Action）</a>。这里的输出是关节角、夹爪位置和开合命令，不是文字回答。抓取是否成功，还取决于碰撞、摩擦和物体是否随手抬起；“发出闭合命令”不等于“已经抓住”。"
    },
    {
      "term": "action prior",
      "kind": "state",
      "source_ids": [
        "report"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "Abstract; Introduction learned sensorimotor priors"
        }
      ],
      "article_quote": "π0.5 从机器人数据中学过抓取、搬运等动作模式，作者将这些已学到的习惯称为动作先验（action prior）。它也可能抓错目标，或者在上一步失败后继续下一步。Astra 可以显式检查目标和执行反馈，但每段都独立构造动作既慢，也不一定稳定。报告要检验的就是两者一起使用是否优于 Astra 独自控制。"
    },
    {
      "term": "teacher / student",
      "kind": "actor",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "robodojo client.py + SOURCE.json runtime model identities; no optimization step"
        }
      ],
      "article_quote": "报告用 System 1 / System 2 类比“熟练动作”和“显式思考”，不是神经结构证明。源码里的 <code>teacher</code> 指 Astra，<code>student</code> 指 π0.5，<strong>两者在这里都没有做蒸馏训练</strong>。对 LLM / Agent 研究更直接的借鉴是怎样提供候选、反馈和受限执行工具。"
    },
    {
      "term": "FK",
      "kind": "operation",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "robodojo_server/kinematics.py; action_edit_kinematics.py; client.py trajectory"
        }
      ],
      "article_quote": "控制程序根据机器人几何计算每步对应的夹爪位置与朝向，即 <a id=\"read-fk\" href=\"#basis-kinematics\">FK（forward kinematics）</a>。这只计算机器人，不预演物体、碰撞或抓取结果。"
    },
    {
      "term": "EEF",
      "kind": "state",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "robodojo EEF interface, target payload and action_edit_kinematics.py"
        }
      ],
      "article_quote": "夹爪这样的末端执行部件称为 <a id=\"read-eef\" href=\"#basis-eef\">EEF（end-effector）</a>。"
    },
    {
      "term": "IK",
      "kind": "operation",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "robodojo local damped-least-squares controller + client.py step ACK loop"
        }
      ],
      "article_quote": "控制程序验证范围并执行；<code>edit/eef</code> 用 <a id=\"read-ik\" href=\"#basis-kinematics\">IK（inverse kinematics）</a> 把夹爪目标转成关节目标。每个实际控制步后，根据测量状态重新计算局部 IK。"
    },
    {
      "term": "execution_status / intent_status",
      "kind": "state",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "gate_assessment.py lines 8–31, 33–64"
        }
      ],
      "article_quote": "Astra 必须先报告两种状态：<code>execution_status</code> 说上一段是否进展、失败或仍不确定；<code>intent_status</code> 说下一段候选是否符合当前目标。例如物体没有随夹爪抬起是执行证据；尚未抓住就开始运往篮子，是下一步的前置条件有问题。候选的“意图”是从运动建议推断的，不是读取 π0.5 的内部思维。"
    },
    {
      "term": "root point",
      "kind": "state",
      "source_ids": [
        "native"
      ],
      "source_locators": [
        {
          "source_id": "native",
          "locator": "env/reward_manager/func_parser.py is_A_in_B; classify task run_reward"
        }
      ],
      "article_quote": "所核查的 RoboDojo 版本中，<code>run_reward()</code> 要求：三组物体全部在各自篮子范围内，物体参考点不高于篮子包围盒顶部 1 cm 以上，双臂归位。具体的“在篮内”检查是物体 <code>root point</code>（模型坐标系的参考点，不一定是重心）投影在篮子水平多边形内，且高于其底部；它不检查物体整个网格都在容器内部。归位容差是每个位置坐标偏差 ≤15 cm、朝向差 ≤20°。"
    },
    {
      "term": "Score",
      "kind": "metric",
      "source_ids": [
        "native",
        "results"
      ],
      "source_locators": [
        {
          "source_id": "native",
          "locator": "Task milestone reward manager; report Table 1; missing-score provenance"
        }
      ],
      "article_quote": "记录里的 <code>Score</code> 是任务的部分完成分数，具体规则在下一小节。"
    },
    {
      "term": "25 Hz",
      "kind": "metric",
      "source_ids": [
        "report",
        "code"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "§6.3 physical duration; simulator control contract"
        }
      ],
      "article_quote": "所选运行记录 token 为 624,762,828 / 1,132,343,772，Hybrid 少 44.8%。这包含大量重复的缓存输入，不是账单金额，也不含全部早期重试。<a id=\"read-clock\" href=\"#basis-clock\">25 Hz 控制</a>意味着每控制步对应 0.04 s；Hybrid 平均物理运动 34.20 s、Direct 30.58 s，均排除模型思考的等待。失败早停也会缩短运动时间，不能据此判断谁端到端更快。"
    },
    {
      "term": "native evaluation",
      "kind": "operation",
      "source_ids": [
        "code",
        "native"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "client.py native termination restriction; session.py simulation native checker"
        },
        {
          "source_id": "native",
          "locator": "task run_reward and reward manager verdict"
        }
      ],
      "article_quote": "是否完成由模拟器自带的检查规则判定，报告称为 native evaluation（原生评测）。"
    }
  ],
  "coverage": [
    {
      "id": "central-claim",
      "claim_type": "author-claim",
      "source_ids": [
        "report"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "Abstract; §2.1; §3; §8"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "Astra 的语义判断能否弥补机器人策略的错误，而机器人策略能否补上 Astra 的操作细节？"
        }
      ]
    },
    {
      "id": "action-loop",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "code",
        "report"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "hybrid_rollout/robodojo/robodojo_server/client.py prepare/trajectory/execute; gpt_only_client.py; action_edit_kinematics.py"
        },
        {
          "source_id": "report",
          "locator": "§2.1; Figure 2"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "选择 <code>student</code> 就原样执行候选前 <strong>1–15 步</strong>；选择 <code>edit</code> 就对候选夹爪轨迹加位移、旋转或开合修正，执行 <strong>1–5 步</strong>"
        },
        {
          "artifact": "article",
          "quote": "动作段结束才给 Astra 新观察；候选中没执行的部分丢弃，π0.5 从新状态重新生成。"
        }
      ]
    },
    {
      "id": "gate-boundary",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "hybrid_rollout/robodojo/robodojo_server/gate_assessment.py validate_assessment lines 33–64"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "Python 检查的是 Astra 填的字段与动作范围，不会独立证明它的语义判断正确"
        }
      ]
    },
    {
      "id": "task-provenance",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "report",
        "results"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "§2.2 Task Selection and Evaluation Protocol"
        },
        {
          "source_id": "results",
          "locator": "queries.tasks / case scenario seeds / provenance"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "作者把官方 π0.5 成功率的 0–72% 划为四个等宽区间，从低到高选 6、2、1、1 个任务。十项各跑五次，共 50 次；数字排列、装箱、叠衣服为 2 次标准加 3 次随机场景，其余为五次标准布局。Direct / Hybrid 对齐任务、场景及记录的 seeds（控制随机场景与策略采样的随机种子）；源码不保证完整物理状态逐位一致。"
        }
      ]
    },
    {
      "id": "annotation-and-check-construction",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "native",
        "code"
      ],
      "source_locators": [
        {
          "source_id": "native",
          "locator": "task/RoboDojo/tasks/classify_objects_by_language.py gen_instruction, run_reward, reward_list_init"
        },
        {
          "source_id": "code",
          "locator": "RoboDojo SOURCE.json upstream native revision"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "指令与检查条件都由 benchmark 的 Python 任务代码生成或注册，未另行提供人工逐条标注的判定文件。"
        },
        {
          "artifact": "article",
          "quote": "任务与几何规则是程序编写的，报告未披露独立人工复核或标注一致性研究。"
        }
      ]
    },
    {
      "id": "public-vs-hidden-inputs",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "code"
      ],
      "source_locators": [
        {
          "source_id": "code",
          "locator": "client.py observation_keys/_observation + prepare; prompt_context.py; gate_assessment.py GATE_INSTRUCTION; frozen native_termination"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "执行 Agent 能看到图像、机器人测量、历史、任务说明与完成要求；不能查询隐藏物体真值、未来物理状态或评分来规划，也不能回滚。是否完成由模拟器自带的检查规则判定，报告称为 native evaluation（原生评测）。固定 RoboDojo 案例禁止模型提前宣告停止；基础设施中断与原生失败不是同一种记录。"
        }
      ]
    },
    {
      "id": "evaluation-formulas",
      "claim_type": "reproduced-calculation",
      "source_ids": [
        "results",
        "native"
      ],
      "source_locators": [
        {
          "source_id": "results",
          "locator": "queries.cases; provenance.json score_missingness; article verify_metrics.py"
        },
        {
          "source_id": "native",
          "locator": "milestone values and terminal failure cap"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "Hybrid 为 <code>100 × 31.30 / 50 = 62.60</code>；Direct 为 <code>100 × 18.15 / 48 = 37.8125</code>"
        },
        {
          "artifact": "article",
          "quote": "Direct 有两条未得到原生终态判定的记录：成功率按未成功计入 50 次，Score 则缺失，只用 48 次"
        }
      ]
    },
    {
      "id": "checker-code-and-cases",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "native",
        "results",
        "report"
      ],
      "source_locators": [
        {
          "source_id": "native",
          "locator": "classify_objects_by_language.py run_reward/gen_instruction; func_parser.py is_A_in_B; reward_manager.py max tier per step and failed cap"
        },
        {
          "source_id": "results",
          "locator": "mix__/gpt__classify_objects_by_language__standard__g0__l0"
        },
        {
          "source_id": "report",
          "locator": "Video 1, Decision 29 / 33 / 47"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "所核查的 RoboDojo 版本中，<code>run_reward()</code> 要求：三组物体全部在各自篮子范围内，物体参考点不高于篮子包围盒顶部 1 cm 以上，双臂归位。具体的“在篮内”检查是物体 <code>root point</code>（模型坐标系的参考点，不一定是重心）投影在篮子水平多边形内，且高于其底部；它不检查物体整个网格都在容器内部。归位容差是每个位置坐标偏差 ≤15 cm、朝向差 ≤20°。"
        },
        {
          "artifact": "article",
          "quote": "最终 Hybrid 用 794/1,100 个控制步、73 个动作段，其中 130 步由 Astra 修正，原生结果为成功、Score=100。配对 Direct 用尽 1,100 步、220 段，失败、Score=40。公开视频覆盖了这段行为，公开摘要给出终态；未发布完整逐步 checker 结果，不能进一步断言 Direct 最后究竟哪组物体放错。"
        },
        {
          "artifact": "article",
          "quote": "视频中的 Decision 是 Astra 的决策序号，Control 是累计控制步。Decision 29 接受 π0.5：释放左篮中的绿色汽车并向上撤回。到 Decision 33 / Control 409，Astra 将手里木制玩具的候选方向修正到右侧红篮：左臂位移修正为 <code>(+4.5 cm, 0, +0.1 cm)</code>，维持闭合，执行 5 步。稍后 Decision 47 又接受 π0.5，接近剩下的木制狮子。这说明一次局部纠正怎样接回已有策略，而不是 Astra 接管整题。"
        }
      ]
    },
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        "robolab",
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          "locator": "Table 1 / public 100 selected cases; native completion and success fields"
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          "locator": "models/tasks rates and successes"
        },
        {
          "source_id": "report",
          "locator": "Tables 1–3; Figure 3/4"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "成功率 Hybrid 48%、Direct 26%；π0.5 公开参照为 15.67%，Score 24.43。"
        },
        {
          "artifact": "article",
          "quote": "Direct 49/50、Hybrid 46/50；π0.5 和 Cosmos3-Nano-Policy 各 18/50，DreamZero 17/50。"
        }
      ]
    },
    {
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      "claim_type": "interpretation",
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        "report",
        "code"
      ],
      "source_locators": [
        {
          "source_id": "report",
          "locator": "§1.1 Related Community Explorations; §2 control architecture"
        },
        {
          "source_id": "code",
          "locator": "Both clients share task context and EEF controller; no training code for this method"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "<strong>最接近的路线是通用模型直接控制机器人，以及通用模型调用已训练的动作策略。</strong>原报告的 Related Work 主要梳理社区探索，未给出全面的同条件算法对照。下面按控制方式比较，不跨项目比较成功率。"
        },
        {
          "artifact": "article",
          "quote": "本报告不是只分解任务、调用一次技能；Astra 在每段审查 π0.5 的具体运动建议"
        }
      ]
    },
    {
      "id": "limitations",
      "claim_type": "unknown",
      "source_ids": [
        "report",
        "code",
        "native",
        "robolab"
      ],
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        {
          "source_id": "report",
          "locator": "§5 failures; §7 scope; latency"
        },
        {
          "source_id": "code",
          "locator": "Different action horizons/interfaces; no fixed-factor ablation reported"
        },
        {
          "source_id": "native",
          "locator": "root-point-based containment, task home checks"
        },
        {
          "source_id": "robolab",
          "locator": "notes historical/retries and last two decision-limit changes"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "<strong>报告证明了一个组合系统在所选 RoboDojo 任务上更有效，还没有隔离出收益来自哪项设计。</strong>Direct / Hybrid 同时改变候选来源、动作接口和最长执行段；没有“相同段长、有无候选”的对照，不能把全部提升归于 Astra 的判断，或全部归于 π0.5 的先验。"
        },
        {
          "artifact": "article",
          "quote": "98% 应读作<strong>选定最终记录的描述性成绩</strong>"
        },
        {
          "artifact": "article",
          "quote": "它没有报告真实机器人部署的成功率或实时延迟实验。"
        }
      ]
    },
    {
      "id": "usage-and-time",
      "claim_type": "reproduced-calculation",
      "source_ids": [
        "results",
        "report"
      ],
      "source_locators": [
        {
          "source_id": "results",
          "locator": "cases tokens/control steps/chunks; verified with Python stdlib"
        },
        {
          "source_id": "report",
          "locator": "Table 3 / §6.3 tokens include cached input, selected run scope"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "6,174 / 42,750 = 14.44%"
        },
        {
          "artifact": "article",
          "quote": "所选运行记录 token 为 624,762,828 / 1,132,343,772，Hybrid 少 44.8%。"
        }
      ]
    },
    {
      "id": "robolab-selection",
      "claim_type": "inspected-implementation",
      "source_ids": [
        "robolab",
        "code"
      ],
      "source_locators": [
        {
          "source_id": "robolab",
          "locator": "report_web/robolab.json notes lines 163–170; robolab-baselines.json selection"
        },
        {
          "source_id": "code",
          "locator": "report_baselines.py historical first-five ordering"
        }
      ],
      "evidence": [
        {
          "artifact": "article",
          "quote": "更重要的是协议：Astra 两边包括保留的历史结果与授权重试，初始状态未严格对齐；最后两次 Direct 的 BlocksInBin 重试把决策上限从 180 改到 500（模拟器总步数与成功规则不变）。三个基线取 2026 年 6 月历史记录中每任务按顺序的前五次，包含失败，未核实与 Astra 使用相同任务版本和控制设置。因此 98% 应读作<strong>选定最终记录的描述性成绩</strong>，不能宣称一次尝试、同预算条件下达到 98%。"
        }
      ]
    }
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          "artifact": "deck",
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      "source_locator": "Report behavior section contact; video-selection.json #8 / clip__4288645ef90dc53de13376eb__0",
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      "rationale": "Not locally embedded: shows 3D approach or non-prehensile contact before hand-back; method and Discussion retain contact limits without portraying it as collision simulation. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
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      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__4288645ef90dc53de13376eb__0.mp4",
      "original_range_seconds": [
        16.12,
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    },
    {
      "id": "video-9",
      "kind": "appendix-visual",
      "label": "Video 9 · 数字摆放：发现未终止，重新检查与微调",
      "source_id": "report",
      "source_locator": "Report behavior section reasoning; video-selection.json #9 / clip__cbf8658bad76fd96fef01245__1",
      "status": "omitted",
      "rationale": "Not locally embedded: shows reinspection after non-termination; note distinguishes visual checking from hidden reward/ground-truth access. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__cbf8658bad76fd96fef01245__1.mp4",
      "original_range_seconds": [
        19.64,
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      "video_sha256": "8802c5ffdcc55ab9496429b5caeb6045f6802e36b321bd6d8153bd224561641d"
    },
    {
      "id": "video-10",
      "kind": "appendix-visual",
      "label": "Video 10 · 装箱：发现箱后遗漏，并调整物体姿态",
      "source_id": "report",
      "source_locator": "Report behavior section reasoning; video-selection.json #10 / clip__5436877e6101be2b23b24fc2__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows reinspection after non-termination; note distinguishes visual checking from hidden reward/ground-truth access. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__5436877e6101be2b23b24fc2__0.mp4",
      "original_range_seconds": [
        35.8,
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      "video_sha256": "18a0a9a4edb4d321349fb9f3796f2dd3957918bc65d700bba8acafe7ea830e9c"
    },
    {
      "id": "video-11",
      "kind": "appendix-visual",
      "label": "Video 11 · 数字摆放：根据终止反馈继续修正",
      "source_id": "report",
      "source_locator": "Report behavior section reasoning; video-selection.json #11 / clip__5f52fbae6ce02b95ed5346b2__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows reinspection after non-termination; note distinguishes visual checking from hidden reward/ground-truth access. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__5f52fbae6ce02b95ed5346b2__0.mp4",
      "original_range_seconds": [
        18.28,
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      "video_sha256": "eded0467ea8b3a1896e13b5d006e0cf7765e9d39ff34853e690295e09169fb9b"
    },
    {
      "id": "video-12",
      "kind": "appendix-visual",
      "label": "Video 12 · 搭塔：针对未满足的终态进行二次纠错",
      "source_id": "report",
      "source_locator": "Report behavior section reasoning; video-selection.json #12 / clip__b0b8456f0b4d549bc4d56cfe__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows reinspection after non-termination; note distinguishes visual checking from hidden reward/ground-truth access. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__b0b8456f0b4d549bc4d56cfe__0.mp4",
      "original_range_seconds": [
        27.4,
        35.12
      ],
      "video_sha256": "6d5447238da6c5bd24b6fbd992db20c74d5df7462ca1ae7870430eb088ab9b9a"
    },
    {
      "id": "video-13",
      "kind": "appendix-visual",
      "label": "Video 13 · 容器边缘净空不足，搬运时发生碰撞",
      "source_id": "report",
      "source_locator": "Report behavior section failures; video-selection.json #13 / clip__cb2554914fe8187ac98e9e45__0",
      "status": "omitted",
      "rationale": "Not locally embedded: provides a failure example; visible Discussion retains missed objects, rim collision and delayed within-segment feedback as unresolved limits. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__cb2554914fe8187ac98e9e45__0.mp4",
      "original_range_seconds": [
        47.44,
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      "video_sha256": "e4a4f4a3315e660d990e1cc763c2d5283e4b625ca14c51d962cf177ef4e64a26"
    },
    {
      "id": "video-14",
      "kind": "appendix-visual",
      "label": "Video 14 · 滑落发生在动作段内，纠错反馈滞后",
      "source_id": "report",
      "source_locator": "Report behavior section failures; video-selection.json #14 / clip__7ef164f7a8783f3af3eb9090__0",
      "status": "omitted",
      "rationale": "Not locally embedded: provides a failure example; visible Discussion retains missed objects, rim collision and delayed within-segment feedback as unresolved limits. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__7ef164f7a8783f3af3eb9090__0.mp4",
      "original_range_seconds": [
        17.96,
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      ],
      "video_sha256": "33dd8e13d8f72dbb6c1e9959da0f0228762ebe0e52b893fa3c020a2a7cbfc830"
    },
    {
      "id": "video-15",
      "kind": "appendix-visual",
      "label": "Video 15 · 复杂抓取反复失败，消耗剩余步数",
      "source_id": "report",
      "source_locator": "Report behavior section failures; video-selection.json #15 / clip__5b7eb4161fbb1a8e5851cf52__0",
      "status": "omitted",
      "rationale": "Not locally embedded: provides a failure example; visible Discussion retains missed objects, rim collision and delayed within-segment feedback as unresolved limits. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__5b7eb4161fbb1a8e5851cf52__0.mp4",
      "original_range_seconds": [
        18.8,
        40.04
      ],
      "video_sha256": "96a27169cdaca680dbe52636982250364aa6da2805dc89c1a2e21cc6e4e8cae3"
    },
    {
      "id": "video-16",
      "kind": "appendix-visual",
      "label": "Video 16 · 麻将操作错误未被及时识别",
      "source_id": "report",
      "source_locator": "Report behavior section failures; video-selection.json #16 / clip__bd5f4382adb568ed22dfca47__0",
      "status": "omitted",
      "rationale": "Not locally embedded: provides a failure example; visible Discussion retains missed objects, rim collision and delayed within-segment feedback as unresolved limits. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__bd5f4382adb568ed22dfca47__0.mp4",
      "original_range_seconds": [
        13.16,
        24.04
      ],
      "video_sha256": "845e6ac55d8eed89308d3e4427f6c0226a013af7c63a64e7d1a03b904d37667c"
    },
    {
      "id": "video-17",
      "kind": "appendix-visual",
      "label": "Video 17 · 零样本方案：尝试用机械臂把瓶子扫入桶中",
      "source_id": "report",
      "source_locator": "Report behavior section gpt-only; video-selection.json #17 / clip__b34c1a832bb5123d6eb6a6af__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows Direct action plans and stability issues; related-work and method distinguish constructing every action from accepting robot-policy candidates. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__b34c1a832bb5123d6eb6a6af__0.mp4",
      "original_range_seconds": [
        0.08,
        28.04
      ],
      "video_sha256": "a186a2356952de5f82cf35c803a9b61dbda53c234c9e970e6cbd6db14abedc98"
    },
    {
      "id": "video-18",
      "kind": "appendix-visual",
      "label": "Video 18 · 零样本方案：单手抓板，搭建不够稳定",
      "source_id": "report",
      "source_locator": "Report behavior section gpt-only; video-selection.json #18 / clip__71c12723687a550b770f36c0__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows Direct action plans and stability issues; related-work and method distinguish constructing every action from accepting robot-policy candidates. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__71c12723687a550b770f36c0__0.mp4",
      "original_range_seconds": [
        1.16,
        11.16
      ],
      "video_sha256": "a22a8bde36988ee7aa09d572730e8dbe166a12cd2b52ee18d14252aee40adf82"
    },
    {
      "id": "video-19",
      "kind": "appendix-visual",
      "label": "Video 19 · 零样本方案：单臂操作的稳定性问题",
      "source_id": "report",
      "source_locator": "Report behavior section gpt-only; video-selection.json #19 / clip__9e40a74ed6b0a356a421f53b__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows Direct action plans and stability issues; related-work and method distinguish constructing every action from accepting robot-policy candidates. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__9e40a74ed6b0a356a421f53b__0.mp4",
      "original_range_seconds": [
        4,
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      ],
      "video_sha256": "52d44abf7ffc74a7c5cf250019043e173c3fd4556f229ddaf6df1c5273687591"
    },
    {
      "id": "video-20",
      "kind": "appendix-visual",
      "label": "Video 20 · 本体信息未被有效利用，控制反复受阻",
      "source_id": "report",
      "source_locator": "Report behavior section direct-control; video-selection.json #20 / clip__faad002fd6c510f09db4c435__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows robot-state utilization or local recovery; foundations and method explain measured state and recomputed local IK. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__faad002fd6c510f09db4c435__0.mp4",
      "original_range_seconds": [
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      ],
      "video_sha256": "5a42554ee72bfe334a5fa5271371359644f429aceb96174c2bc7792095913a32"
    },
    {
      "id": "video-21",
      "kind": "appendix-visual",
      "label": "Video 21 · 数字摆放：理解控制反馈后的精彩恢复",
      "source_id": "report",
      "source_locator": "Report behavior section direct-control; video-selection.json #21 / clip__6ba3a538a3405206181aa6c6__0",
      "status": "omitted",
      "rationale": "Not locally embedded: shows robot-state utilization or local recovery; foundations and method explain measured state and recomputed local IK. Underlying simulator/benchmark media reuse rights not verified; official clip remains linked instead of redistributing footage or frames.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "THIRD_PARTY_NOTICES.md excludes benchmark assets/videos from blanket MIT grant.",
      "credit": "Original recorded demonstration: Su et al.; upstream simulator asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/clips/clip__6ba3a538a3405206181aa6c6__0.mp4",
      "original_range_seconds": [
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        35.56
      ],
      "video_sha256": "a47220a3a46f654ffe4b38c833645910fd43166e77f8aefacd99234f7d20e97a"
    },
    {
      "id": "initial-organize_table",
      "kind": "appendix-visual",
      "label": "Initial-state example · organize_table",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=organize_table / media/tasks/organize_table.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 鼠标、键盘、摆件、闹钟和杂物散布在桌面。 Its task goal is 将指定物品放到各自位置，再打开抽屉收纳剩余杂物，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/organize_table.jpg"
    },
    {
      "id": "initial-classify_objects_by_language",
      "kind": "appendix-visual",
      "label": "Initial-state example · classify_objects_by_language",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=classify_objects_by_language / media/tasks/classify_objects_by_language.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 多个类别的物体混放，篮子的对应关系由当前指令给出。 Its task goal is 按照本条指令的类别—篮子映射放置全部物体，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/classify_objects_by_language.jpg"
    },
    {
      "id": "initial-imitate_sorting_sequence",
      "kind": "appendix-visual",
      "label": "Initial-state example · imitate_sorting_sequence",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=imitate_sorting_sequence / media/tasks/imitate_sorting_sequence.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 场景先提供一段物体排序示范。 Its task goal is 先观察并记住示范，再按照相同顺序放置相应物体，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/imitate_sorting_sequence.jpg"
    },
    {
      "id": "initial-arrange_largest_number",
      "kind": "appendix-visual",
      "label": "Initial-state example · arrange_largest_number",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=arrange_largest_number / media/tasks/arrange_largest_number.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 数字块散落在目标垫附近。 Its task goal is 从左到右组成最大的数字，校正朝向并放在目标垫上，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/arrange_largest_number.jpg"
    },
    {
      "id": "initial-pack_objects_into_box",
      "kind": "appendix-visual",
      "label": "Initial-state example · pack_objects_into_box",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=pack_objects_into_box / media/tasks/pack_objects_into_box.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 多个不同形状的物体分布在箱子周围。 Its task goal is 将所有物体装进箱中，并满足指令要求的朝向，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/pack_objects_into_box.jpg"
    },
    {
      "id": "initial-classify_objects",
      "kind": "appendix-visual",
      "label": "Initial-state example · classify_objects",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=classify_objects / media/tasks/classify_objects.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 多种物体与三个分类篮摆在桌面上。 Its task goal is 把全部物体按类别分入三个篮子，最后归位双臂。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/classify_objects.jpg"
    },
    {
      "id": "initial-build_tower",
      "kind": "appendix-visual",
      "label": "Initial-state example · build_tower",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=build_tower / media/tasks/build_tower.jpg",
      "status": "omitted",
      "rationale": "Task image depicts 木块与木板尚未组成塔。 Its task goal is 按要求搭建有支撑的层叠结构，并在归位双臂后保持稳定。 Not redistributed because benchmark rendering assets have unverified downstream media rights. Classification mapping is taught by a separate fact-based blog diagram, not traced or copied from this image.",
      "placements": [],
      "asset_paths": [],
      "permission_status": "unknown",
      "permission_basis": "Benchmark image assets excluded from root MIT documentation grant; no independent reuse license verified.",
      "credit": "Su et al. task catalogue; RoboDojo underlying asset rights retained.",
      "original_url": "https://anonymous-report-421.github.io/public-website/media/tasks/build_tower.jpg"
    },
    {
      "id": "initial-make_kong",
      "kind": "appendix-visual",
      "label": "Initial-state example · make_kong",
      "source_id": "report",
      "source_locator": "§2 task catalogue / queries.tasks.rows id=make_kong / media/tasks/make_kong.jpg",
      "status": "omitted",
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