{
  "name": "物理 AI 硬體選型表",
  "version": "v1.0",
  "updatedAt": "2026-08-19",
  "method": [
    "先從任務、資料、控制責任與驗收條件反推硬體，不以單一產品跑分排名。",
    "高階 AI 推理、即時控制與獨立安全機制必須分層，不把模型當成安全控制器。",
    "每個情境都要在代表性場域量測最差延遲、故障與人工接管，而不是只看平均效能。"
  ],
  "limitations": [
    "這不是品牌產品排名、價格表、供貨資訊、效能保證或安全認證。",
    "實際平台選擇仍須核對官方規格、軟體相容性、感測器介面、場域條件與 PoC 量測。"
  ],
  "records": [
    {
      "id": "robotic-manipulation",
      "scenario": "機械手臂抓取、分揀或精密操作",
      "firstDecision": "物件範圍、速度、力量、可用空間與人員邊界",
      "hardwareFocus": "相機或深度、力覺、推理平台、即時控制器、獨立安全層與致動器介面",
      "pocMeasurements": "感測同步、p95與最差延遲、重試、停止與回安全位置",
      "doNotInfer": "VLA或GPU可以取代低階控制、急停或安全認證",
      "relatedGuide": "/guides/physical-ai-hardware/"
    },
    {
      "id": "mobile-robot",
      "scenario": "AMR、移動平台或巡檢設備",
      "firstDecision": "地圖、速度、場域變化、人員偵測、斷網後的行為",
      "hardwareFocus": "定位與感測器同步、場域邊緣運算、網路備援、電池與散熱",
      "pocMeasurements": "端到端延遲與抖動、掉幀、定位失效、續航與降級策略",
      "doNotInfer": "桌面工作站跑得動，就能直接裝到移動載具",
      "relatedGuide": "/guides/jetson-orin-vs-thor/"
    },
    {
      "id": "teleoperation-data",
      "scenario": "遙操作與資料採集",
      "firstDecision": "示範覆蓋範圍、成功或失敗標記、保存期限與版本責任",
      "hardwareFocus": "相機、深度、力覺、時間戳、同步、儲存、網路與操控介面",
      "pocMeasurements": "資料遺失率、校正、時間對齊、事件可追溯性與標註成本",
      "doNotInfer": "收集到影片，就已經能訓練或驗收機器人行為",
      "relatedGuide": "/guides/lerobot-hardware/"
    },
    {
      "id": "vla-development",
      "scenario": "VLA、視覺模型或策略開發",
      "firstDecision": "模型版本、輸入格式、context、資料批次、訓練與推論邊界",
      "hardwareFocus": "工作站GPU或VRAM、系統RAM、儲存、網路與可重跑的開發環境",
      "pocMeasurements": "模型記憶體、資料吞吐、迭代時間、版本對應與代表性測試集",
      "doNotInfer": "訓練主機的容量或模型參考，就等於上機即時需求",
      "relatedGuide": "/guides/vla/"
    },
    {
      "id": "simulation-synthetic-data",
      "scenario": "模擬、合成資料與數位孿生",
      "firstDecision": "哪些物理、感測或場域差異會改變決策結果",
      "hardwareFocus": "模擬工作站、GPU或VRAM、資料儲存、場景資產與真實資料回放",
      "pocMeasurements": "模擬重現性、reality gap、真實資料覆蓋與版本回歸",
      "doNotInfer": "模擬通過或畫面逼真，就代表真機可安全上線",
      "relatedGuide": "/guides/robotics-simulation-synthetic-data/"
    },
    {
      "id": "enterprise-poc-operations",
      "scenario": "企業封閉PoC到小規模營運",
      "firstDecision": "任務基線、驗收門檻、owner、人工接管、回復與維護責任",
      "hardwareFocus": "場域推理平台、控制與安全分層、遙測、儲存、網路、備援與維修介面",
      "pocMeasurements": "任務成功率、最差延遲、人工介入率、故障回復、設備狀態與成本",
      "doNotInfer": "Demo成功一次，就可以擴大採購或省略安全與維運設計",
      "relatedGuide": "/guides/enterprise-physical-ai/"
    }
  ],
  "sources": [
    {
      "label": "NVIDIA Physical AI Learning",
      "url": "https://docs.nvidia.com/learning/physical-ai/index.html"
    },
    {
      "label": "NVIDIA Jetson Software Architecture",
      "url": "https://docs.nvidia.com/jetson/archives/r38.2/DeveloperGuide/AR/JetsonSoftwareArchitecture.html"
    },
    {
      "label": "ROS 2 Introduction to Real-time Systems",
      "url": "https://design.ros2.org/articles/realtime_background.html"
    },
    {
      "label": "Google DeepMind Gemini Robotics",
      "url": "https://deepmind.google/en/models/gemini-robotics/gemini-robotics/"
    }
  ]
}