{"id":65527,"date":"2026-01-25T08:04:34","date_gmt":"2026-01-25T00:04:34","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/65527.html"},"modified":"2026-01-25T08:04:34","modified_gmt":"2026-01-25T00:04:34","slug":"%e5%9c%a8-headless-%e6%9c%8d%e5%8a%a1%e5%99%a8%e4%b8%8a%e8%b7%91%e9%80%9a-maniskill-act%e5%85%a8%e6%b5%81%e7%a8%8b","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/65527.html","title":{"rendered":"\u5728 Headless \u670d\u52a1\u5668\u4e0a\u8dd1\u901a ManiSkill + ACT\u5168\u6d41\u7a0b"},"content":{"rendered":"

<\/h2>\n

📖 0. \u524d\u8a00<\/h3>\n

\u5728\u673a\u5668\u4eba\u5b66\u4e60（Robot Learning）\u9886\u57df，ManiSkill \u662f\u76ee\u524d\u6700\u5148\u8fdb\u7684\u901a\u7528\u4eff\u771f\u5e73\u53f0\u4e4b\u4e00，\u800c ACT (Action Chunking with Transformers) \u662f\u6a21\u4eff\u5b66\u4e60\u9886\u57df\u7684\u7b97\u6cd5\u3002<\/p>\n

\u5b98\u65b9\u6587\u6863\u901a\u5e38\u63cf\u7ed8\u4e86\u4e00\u6761\u201c\u5feb\u4e50\u8def\u5f84（Happy Path）\u201d：\u4e0b\u8f7d\u6570\u636e -> \u8fd0\u884c\u547d\u4ee4 -> \u6210\u529f\u3002\u7136\u800c，\u5728\u771f\u5b9e\u7684\u79d1\u7814\u751f\u4ea7\u73af\u5883\u4e2d（\u7279\u522b\u662f\u65e0\u663e\u793a\u5668\u7684 Linux \u670d\u52a1\u5668），\u6211\u4eec\u9762\u4e34\u7740\u4e09\u5927\u5de5\u7a0b\u9e3f\u6c9f：<\/p>\n

  • \n

    \u6e32\u67d3：Headless \u670d\u52a1\u5668\u65e0\u6cd5\u76f4\u63a5\u8c03\u7528 GPU \u8fdb\u884c Vulkan \u6e32\u67d3（\u5f53\u7136\u6211\u5176\u5b9e\u53ef\u4ee5，\u4f46\u662f\u4e5f\u5199\u4e00\u4e0b\u65b9\u4fbf\u5176\u4ed6\u4eba\u7528）\u3002<\/p>\n<\/li>\n

  • \n

    \u6570\u636e：ManiSkill \u7684\u5b58\u50a8\u683c\u5f0f（\u5b57\u5178\/State）\u4e0e ACT \u7684\u8f93\u5165\u683c\u5f0f（\u6570\u7ec4\/Image）\u4e0d\u517c\u5bb9\u3002<\/p>\n<\/li>\n

  • \n

    \u7ef4\u5ea6：\u4eff\u771f\u73af\u5883\u7684\u5411\u91cf\u5316\u7279\u6027\u5bfc\u81f4\u7684\u6570\u636e\u7ef4\u5ea6\u9519\u4f4d\u3002<\/p>\n<\/li>\n

    \u672c\u6587\u5c06\u8be6\u7ec6\u8bb0\u5f55\u5982\u4f55\u586b\u5e73\u8fd9\u4e9b\u5751，\u5b9e\u73b0 ACT \u89c6\u89c9\u6a21\u578b\u7684\u6210\u529f\u8bad\u7ec3\u3002<\/p>\n

    🧠 \u7b2c\u4e00\u90e8\u5206：\u6838\u5fc3\u539f\u7406<\/h3>\n

    \u5728\u52a8\u624b\u4e4b\u524d，\u6211\u4eec\u5fc5\u987b\u7406\u89e3\u6211\u4eec\u5728\u505a\u4ec0\u4e48\u3002<\/p>\n

    1.1 \u4ec0\u4e48\u662f\u6a21\u4eff\u5b66\u4e60 (Imitation Learning, IL)？<\/h4>\n

    \u4e0e\u5f3a\u5316\u5b66\u4e60（RL）\u901a\u8fc7\u201c\u8bd5\u9519-\u5956\u52b1\u201d\u6765\u5b66\u4e60\u4e0d\u540c，\u8be6\u7ec6\u5185\u5bb9\u81ea\u67e5\u3002<\/p>\n

    1.2 \u4e3a\u4ec0\u4e48\u9009\u62e9 ACT？(VS \u4f20\u7edf Behavior Cloning)<\/h4>\n

    \u4f20\u7edf\u7684\u884c\u4e3a\u514b\u9686（BC）\u662f\u5355\u6b65\u9884\u6d4b：<\/p>\n

    \u3002\u8fd9\u6709\u4e2a\u81f4\u547d\u5f31\u70b9：\u4e00\u65e6\u67d0\u4e00\u6b65\u9884\u6d4b\u6709\u5fae\u5c0f\u8bef\u5dee，\u673a\u5668\u4eba\u5c31\u4f1a\u504f\u79bb\u8f68\u8ff9，\u8fdb\u5165\u4ece\u672a\u89c1\u8fc7\u7684\u72b6\u6001（Distribution Shift），\u5bfc\u81f4\u8bef\u5dee\u50cf\u6eda\u96ea\u7403\u4e00\u6837\u7d2f\u79ef\u3002<\/p>\n

    ACT (Action Chunking with Transformers) \u5f15\u5165\u4e86\u4e24\u4e2a\u5173\u952e\u6539\u8fdb：<\/p>\n

  • \n

    Action Chunking（\u52a8\u4f5c\u5206\u5757）：\u4e00\u6b21\u9884\u6d4b\u672a\u6765 k \u6b65\u7684\u52a8\u4f5c\u5e8f\u5217<\/p>\n<\/li>\n

  • \n

    CVAE + Transformer：\u4f7f\u7528 CVAE \u5efa\u6a21\u52a8\u4f5c\u7684\u591a\u6a21\u6001\u5206\u5e03（\u540c\u4e00\u4e2a\u4efb\u52a1\u6709\u591a\u79cd\u505a\u6cd5），\u4f7f\u7528 Transformer \u5904\u7406\u65f6\u5e8f\u4f9d\u8d56\u3002<\/p>\n<\/li>\n

    1.3 \u4ec0\u4e48\u662f Motion Planning？\u5b83\u4ece\u54ea\u91cc\u6765？<\/h4>\n

    \u6211\u4eec\u4e0b\u8f7d\u7684\u6570\u636e\u5e26\u6709 motionplanning \u6807\u7b7e\u3002\u8fd9\u610f\u5473\u7740\u8fd9\u4e9b\u201c\u4e13\u5bb6\u6570\u636e\u201d\u4e0d\u662f\u4eba\u7c7b\u624b\u64cd\u7684，\u800c\u662f\u7531\u7b97\u6cd5\u751f\u6210\u7684\u3002<\/p>\n

      \n
    • \n

      \u539f\u7406：\u57fa\u4e8e IK (\u9006\u8fd0\u52a8\u5b66) \u7b49\u6570\u5b66\u7b97\u6cd5\u3002<\/p>\n<\/li>\n

    • \n

      \u7279\u70b9：\u5b83\u62e5\u6709\u73af\u5883\u7684\u7edd\u5bf9\u51e0\u4f55\u4fe1\u606f，\u7b97\u51fa\u7684\u8f68\u8ff9\u662f\u7269\u7406\u53ef\u884c\u4e14\u65e0\u78b0\u649e\u7684\u3002<\/p>\n<\/li>\n

    • \n

      \u4ef7\u503c：\u5b83\u662f ACT \u7684\u8001\u5e08\u3002\u6211\u4eec\u7528 ACT \u8bad\u7ec3\u51fa\u7684\u795e\u7ecf\u7f51\u7edc，\u672c\u8d28\u4e0a\u662f\u5728\u84b8\u998f\u8fd0\u52a8\u89c4\u5212\u7b97\u6cd5\u7684\u77e5\u8bc6，\u5c06\u5176\u8f6c\u5316\u4e3a\u4e00\u4e2a\u80fd\u901a\u8fc7\u89c6\u89c9\u5b9e\u65f6\u53cd\u5e94\u7684\u7b56\u7565\u3002<\/p>\n<\/li>\n<\/ul>\n

      1.4 State vs RGBD：\u4e24\u79cd\u89c2\u6d4b\u6a21\u5f0f\u7684\u672c\u8d28\u533a\u522b<\/h4>\n

      \u8fd9\u662f\u672c\u6d41\u7a0b\u4e2d\u6700\u5173\u952e\u7684\u9009\u62e9\u3002<\/p>\n\n\n\n\n\n\n\n
      \u7279\u6027<\/td>\nState (\u72b6\u6001)<\/td>\nRGBD (\u89c6\u89c9)<\/td>\n<\/tr>\n
      \u5b9a\u4e49<\/td>\n\u4e0a\u5e1d\u89c6\u89d2\u3002\u76f4\u63a5\u8bfb\u53d6\u7269\u4f53\u7684 XYZ \u5750\u6807\u3001\u65cb\u8f6c\u56db\u5143\u6570\u3001\u5173\u8282\u89d2\u5ea6\u3002<\/td>\n\u771f\u5b9e\u89c6\u89d2\u3002\u53ea\u80fd\u770b\u5230\u6444\u50cf\u5934\u62cd\u6444\u7684 RGB \u56fe\u50cf\u548c\u6df1\u5ea6\u56fe\u3002<\/td>\n<\/tr>\n
      \u6570\u636e\u5f62\u6001<\/td>\n\u7ed3\u6784\u5316\u5b57\u5178 (Dict) \u6216\u4f4e\u7ef4\u5411\u91cf\u3002<\/td>\n\u9ad8\u7ef4\u5f20\u91cf (Tensor)，\u5982 (3, 128, 128)\u3002<\/td>\n<\/tr>\n
      ACT \u517c\u5bb9\u6027<\/td>\n\u5dee\u3002\u5b98\u65b9 ACT \u4ee3\u7801\u9884\u8bbe\u8f93\u5165\u662f\u56fe\u7247，\u5904\u7406 State \u9700\u8981\u9b54\u6539\u4ee3\u7801\u3002<\/td>\n\u5b8c\u7f8e\u3002ACT \u539f\u751f\u5c31\u662f\u4e3a\u89c6\u89c9\u8bbe\u8ba1\u7684\u3002<\/td>\n<\/tr>\n
      Sim-to-Real<\/td>\n\u6781\u96be\u3002\u73b0\u5b9e\u4e2d\u5f88\u96be\u5b9e\u65f6\u83b7\u53d6\u7269\u4f53\u7cbe\u786e\u5750\u6807\u3002<\/td>\n\u6807\u51c6\u8def\u5f84\u3002\u73b0\u5b9e\u4e2d\u88c5\u4e2a\u6444\u50cf\u5934\u5c31\u80fd\u7528\u3002<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u7ed3\u8bba：\u6211\u4eec\u5fc5\u987b\u5728\u670d\u52a1\u5668\u4e0a\u8dd1\u901a RGBD \u6a21\u5f0f，\u5f53\u7136Maniskill\u63d0\u4f9b\u7684\u662fstate\u6a21\u5f0f\u3002<\/p>\n

      \u2699\ufe0f \u7b2c\u4e8c\u90e8\u5206：Environment<\/h3>\n

      \u5728 Headless \u670d\u52a1\u5668\u4e0a\u8fd0\u884c ManiSkill \u7684 SAPIEN \u6e32\u67d3\u5668，\u5fc5\u987b\u89e3\u51b3 Vulkan \u9a71\u52a8\u95ee\u9898\u3002<\/p>\n

      2.1 \u62a5\u9519\u73b0\u8c61<\/h4>\n

      \u8fd0\u884c\u4ee3\u7801\u65f6\u51fa\u73b0：UserWarning: Failed to find Vulkan ICD file\u3002\u8fd9\u4f1a\u5bfc\u81f4\u6e32\u67d3\u51fa\u7684\u56fe\u7247\u5168\u9ed1，\u6216\u8005\u7a0b\u5e8f\u76f4\u63a5\u5d29\u6e83\u3002<\/p>\n

      2.2 \u89e3\u51b3\u65b9\u6848：\u73af\u5883\u53d8\u91cf\u6ce8\u5165<\/h4>\n

      1. \u6838\u5fc3\u4fee\u590d：\u6307\u5b9a Vulkan ICD (Installable Client Driver)<\/p>\n

      \u5e38\u89c1\u8def\u5f84：\/etc\/vulkan\/icd.d\/nvidia_icd.json \u6216 \/usr\/share\/vulkan\/icd.d\/export VK_ICD_FILENAMES=\/etc\/vulkan\/icd.d\/nvidia_icd.json 2. \u6743\u9650\u89e3\u9501：\u5141\u8bb8 Docker\/\u5bb9\u5668 \u8bbf\u95ee\u6240\u6709 GPU \u529f\u80fd<\/p>\n

      NVIDIA_VISIBLE_DEVICES=all export NVIDIA_DRIVER_CAPABILITIES=all,compute,utility,graphics 3. \u8d44\u6e90\u9694\u79bb：\u6307\u5b9a\u4f7f\u7528\u7a7a\u95f2\u7684 GPU (\u5982 ID 6)export CUDA_VISIBLE_DEVICES=6<\/p>\n

      \n

      🌉 \u7b2c\u4e09\u90e8\u5206：\u6570\u636e\u751f\u4ea7\u4e0e\u6e05\u6d17 (Bridge)<\/h3>\n

      \u6211\u4eec\u5fc5\u987b\u624b\u52a8\u7f16\u5199\u811a\u672c，\u8fde\u63a5\u201c\u539f\u59cb\u6570\u636e\u201d\u4e0e\u201cACT \u4ee3\u7801\u201d\u3002<\/p>\n

      ACT \u7684 train.py \u662f\u4e00\u4e2a\u9759\u6001\u52a0\u8f7d\u5668\u3002\u5b83\u6253\u5f00 .h5 \u6587\u4ef6\u540e，\u671f\u671b\u76f4\u63a5\u8bfb\u53d6\u5230\u540d\u4e3a images \u7684\u6570\u636e\u96c6\u3002 \u7136\u800c，ManiSkill \u4e3a\u4e86\u8282\u7701\u5b58\u50a8\u7a7a\u95f4，\u4e0b\u8f7d\u7684\u539f\u59cb .h5 \u53ea\u5305\u542b\u201c\u5267\u672c\u201d（\u5173\u8282\u89d2\u5ea6 + \u7269\u4f53\u5750\u6807），\u6ca1\u6709\u201c\u753b\u9762\u201d\u3002<\/p>\n

      \u76f4\u63a5\u8fd0\u884c\u7684\u540e\u679c：<\/p>\n

      TypeError: new(): data must be a sequence (got dict)<\/p>\n

      \u56e0\u4e3a\u4ee3\u7801\u8bd5\u56fe\u8bfb\u53d6 sensor_data (\u56fe\u7247)，\u7ed3\u679c\u8bfb\u5230\u4e86 obs (\u5750\u6807\u5b57\u5178)\u3002<\/p>\n

      3.2 \u89e3\u51b3\u65b9\u6848：Replay & Render (\u91cd\u653e\u4e0e\u6e32\u67d3)<\/h4>\n

      \u6211\u4eec\u4e0d\u80fd\u51ed\u7a7a\u53d8\u51fa\u56fe\u7247，\u4f46\u6211\u4eec\u53ef\u4ee5\u91cd\u653e\u3002<\/p>\n

      \u6211\u4eec\u9700\u8981\u7f16\u5199\u4e00\u4e2a Python \u811a\u672c (make_rgbd_data.py)，\u5b83\u7684\u903b\u8f91\u5982\u4e0b：<\/p>\n

    • \n

      \u52a0\u8f7d：\u8bfb\u53d6\u539f\u59cb .h5 \u4e2d\u7684 action \u548c env_state\u3002<\/p>\n<\/li>\n

    • \n

      \u642d\u5efa：\u4f7f\u7528 gym.make(…, obs_mode="rgbd") \u542f\u52a8\u4eff\u771f\u5668\u3002<\/p>\n<\/li>\n

    • \n

      \u62cd\u6444：<\/p>\n

    • \n

      env.reset() \u56de\u5230\u521d\u59cb\u72b6\u6001\u3002<\/p>\n<\/li>\n

    • \n

      \u6267\u884c env.step(action) \u91cd\u73b0\u6bcf\u4e00\u4e2a\u52a8\u4f5c\u3002<\/p>\n<\/li>\n

    • \n

      SAPIEN \u5f15\u64ce\u5229\u7528 GPU \u5b9e\u65f6\u6e32\u67d3\u51fa\u5f53\u524d\u5e27\u7684 RGBD \u56fe\u50cf\u3002<\/p>\n<\/li>\n<\/li>\n

    • \n

      \u540e\u671f\u5236\u4f5c：\u5c06\u6e32\u67d3\u51fa\u7684\u56fe\u7247\u6570\u7ec4\u5b58\u5165\u65b0\u7684 .h5 \u6587\u4ef6\u3002<\/p>\n<\/li>\n

      3.3 \u8e29\u5751：\u4e09\u4e2a\u201c\u7ef4\u5ea6\u201d\u7684\u6559\u8bad<\/h4>\n

      \u5728\u7f16\u5199\u8fd9\u4e2a\u811a\u672c\u65f6，\u6211\u9047\u5230\u4e86\u4e09\u4e2a\u7531\u4e8e ManiSkill v3 \u7279\u6027\u5bfc\u81f4\u7684\u4e25\u91cd Bug，\u8fd9\u5728\u5b98\u65b9\u6587\u6863\u4e2d\u672a\u88ab\u63d0\u53ca\u3002<\/p>\n

      🐛 Bug 1 : \u5411\u91cf\u5316\u7ef4\u5ea6\u7684\u9677\u9631<\/h5>\n
        \n
      • \n

        \u73b0\u8c61：ValueError: axes don't match array\u3002<\/p>\n<\/li>\n

      • \n

        \u539f\u56e0：ManiSkill v3 \u9ed8\u8ba4\u662f\u5411\u91cf\u5316\u73af\u5883 (Vectorized Env)\u3002\u5373\u4f7f\u53ea\u8dd1 1 \u4e2a\u73af\u5883，\u8fd4\u56de\u7684\u6570\u636e\u4e5f\u662f\u5e26 Batch \u7ef4\u5ea6\u7684 (1, 128, 128, 3)\u3002<\/p>\n<\/li>\n

      • \n

        \u4fee\u590d：\u5728\u8f6c\u7f6e\u4e4b\u524d，\u5fc5\u987b\u624b\u52a8\u964d\u7ef4\u3002<\/p>\n<\/li>\n<\/ul>\n

        if raw_rgb.ndim == 4: raw_rgb = raw_rgb[0] # (1, H, W, C) -> (H, W, C)<\/p>\n

        🐛 Bug 2 : \u5173\u8282\u6570\u636e\u7684\u7ef4\u5ea6<\/h5>\n
          \n
        • \n

          \u73b0\u8c61：\u8bad\u7ec3\u65f6 loss \u5f02\u5e38\u6216\u62a5\u9519\u3002<\/p>\n<\/li>\n

        • \n

          \u539f\u56e0：\u540c\u7406，qpos \u8fd4\u56de\u7684\u662f (1, 7)，\u800c PyTorch Dataset \u671f\u671b (7,)\u3002<\/p>\n<\/li>\n

        • \n

          \u4fee\u590d：<\/p>\n<\/li>\n<\/ul>\n

          if q.ndim == 2: q = q[0]<\/p>\n

          🐛 Bug 3 : env_states \u7684\u7ed3\u6784\u53d8\u66f4<\/h5>\n
            \n
          • \n

            \u73b0\u8c61：TypeError: Accessing a group … with int\u3002<\/p>\n<\/li>\n

          • \n

            \u539f\u56e0：ManiSkill v3 \u5c06 env_states \u4ece Dataset \u6539\u4e3a\u4e86 Group（\u5c42\u7ea7\u5316\u5b58\u50a8）\u3002\u65e7\u7248\u811a\u672c\u7528 [0] \u7d22\u5f15\u4f1a\u62a5\u9519\u3002<\/p>\n<\/li>\n

          • \n

            \u4fee\u590d：\u7f16\u5199\u9012\u5f52\u51fd\u6570\u6765\u63d0\u53d6\u7b2c\u4e00\u5e27\u72b6\u6001\u3002<\/p>\n<\/li>\n<\/ul>\n

            def get_first_state(h5_node):if isinstance(h5_node, h5py.Group): return {k: get_first_state(v) for k, v in h5_node.items()} return h5_node[0]<\/p>\n

            \n

            🚀 \u7b2c\u56db\u90e8\u5206：\u6700\u7ec8\u6267\u884c SOP<\/h3>\n

            \u5c06\u4e0a\u8ff0\u6240\u6709\u77e5\u8bc6\u6c47\u603b，\u4ee5\u4e0b\u662f \u53ef\u4ee5\u76f4\u63a5\u6267\u884c\u7684\u6807\u51c6\u6d41\u7a0b\u3002<\/p>\n

            Step 1: \u51c6\u5907\u6570\u636e\u751f\u6210\u811a\u672c<\/h4>\n

            \u521b\u5efa make_rgbd_data.py，\u586b\u5165\u5305\u542b\u4e0a\u8ff0\u6240\u6709\u4fee\u590d\u903b\u8f91\u7684\u4ee3\u7801\u3002 (\u6838\u5fc3\u4ee3\u7801\u903b\u8f91：Reset Env -> Loop Actions -> Step & Render -> Save Images)<\/p>\n

            Step 2: \u6267\u884c\u6570\u636e\u8f6c\u6362<\/h4>\n

            export VK_ICD_FILENAMES=\/etc\/vulkan\/icd.d\/nvidia_icd.json python make_rgbd_data.py<\/p>\n

            \u7ed3\u679c：\u751f\u6210 trajectory_rgbd.h5，\u5305\u542b 1000 \u6761\u9ad8\u8d28\u91cf RGBD \u8f68\u8ff9\u3002<\/p>\n

            Step 3: \u914d\u7f6e\u6587\u4ef6\u540c\u6b65<\/h4>\n

            cd ~\/.maniskill\/demos\/PushCube-v1\/motionplanning\/ # \u590d\u5236\u5e76\u91cd\u547d\u540d\u914d\u7f6e，\u786e\u4fdd obs_mode \u4e3a rgbdecho '{…"obs_mode": "rgbd"…}' > trajectory_rgbd.json<\/p>\n

            Step 4: \u542f\u52a8\u8bad\u7ec3<\/h4>\n

            cd ~\/cj\/ManiSkill python examples\/baselines\/act\/train.py \\\\ –env-id "PushCube-v1" \\\\ –demo-path ~\/.maniskill\/demos\/PushCube-v1\/motionplanning\/trajectory_rgbd.h5 \\\\ –control-mode "pd_joint_pos" \\\\ –num-demos 1000 \\\\ –total-iters 30000 \\\\ –exp-name "act_rgbd_final" \\\\ –no-track<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

            📖 0. \u524d\u8a00
            \n\u5728\u673a\u5668\u4eba\u5b66\u4e60（Robot Learning）\u9886\u57df，ManiSkill \u662f\u76ee\u524d\u6700\u5148\u8fdb\u7684\u901a\u7528\u4eff\u771f\u5e73\u53f0\u4e4b\u4e00，\u800c ACT (Action Chunking with Transformers) \u662f\u6a21\u4eff\u5b66\u4e60\u9886\u57df\u7684\u7b97\u6cd5\u3002
            \n\u5b98\u65b9\u6587\u6863\u901a\u5e38\u63cf\u7ed8\u4e86\u4e00\u6761\u201c\u5feb\u4e50\u8def\u5f84（Happy Path）\u201d：\u4e0b\u8f7d\u6570\u636e -> \u8fd0\u884c\u547d\u4ee4 -> \u6210\u529f\u3002\u7136\u800c，\u5728\u771f\u5b9e\u7684\u79d1\u7814\u751f\u4ea7\u73af<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50,427],"topic":[],"class_list":["post-65527","post","type-post","status-publish","format-standard","hentry","category-server","tag-50","tag-427"],"yoast_head":"\n\u5728 Headless \u670d\u52a1\u5668\u4e0a\u8dd1\u901a ManiSkill + ACT\u5168\u6d41\u7a0b - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/65527.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5728 Headless \u670d\u52a1\u5668\u4e0a\u8dd1\u901a ManiSkill + ACT\u5168\u6d41\u7a0b - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"📖 0. \u524d\u8a00 \u5728\u673a\u5668\u4eba\u5b66\u4e60（Robot Learning）\u9886\u57df，ManiSkill \u662f\u76ee\u524d\u6700\u5148\u8fdb\u7684\u901a\u7528\u4eff\u771f\u5e73\u53f0\u4e4b\u4e00，\u800c ACT (Action Chunking with Transformers) \u662f\u6a21\u4eff\u5b66\u4e60\u9886\u57df\u7684\u7b97\u6cd5\u3002 \u5b98\u65b9\u6587\u6863\u901a\u5e38\u63cf\u7ed8\u4e86\u4e00\u6761\u201c\u5feb\u4e50\u8def\u5f84（Happy Path）\u201d：\u4e0b\u8f7d\u6570\u636e -> \u8fd0\u884c\u547d\u4ee4 -> \u6210\u529f\u3002\u7136\u800c，\u5728\u771f\u5b9e\u7684\u79d1\u7814\u751f\u4ea7\u73af\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/65527.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-25T00:04:34+00:00\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/65527.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/65527.html\",\"name\":\"\u5728 Headless \u670d\u52a1\u5668\u4e0a\u8dd1\u901a ManiSkill + ACT\u5168\u6d41\u7a0b - 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