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=============================

Kerloud 绯诲垪鏃犱汉鏈烘彁渚涗赴瀵岀殑閰嶇疆閫夐」锛屽彲婊¤冻涓嶅悓鍦烘櫙涓嬬殑闇€姹傘€�

涓嶅悓鍨嬪彿鐨勫姛鑳藉拰鐢ㄦ埛浜虹兢璇存槑瑙佷笅琛紝


.. list-table::
   :header-rows: 1
   :widths: 10 20 35 35

   * - 搴忓彿
     - 鍨嬪彿
     - 涓昏鍔熻兘
     - 閫傚悎鐢ㄦ埛
   * - 1
     - :ref:`Kerloud Pi Indoor <kerloud_pi_indoor_option_zh>`
     - 鏍戣帗娲炬満杞界數鑴�, 鍏夋祦瀹氫綅
     - 鍏ラ棬鐢ㄦ埛锛屽鍐呭簲鐢ㄥ満鏅紝
       杩涜鏈鸿浇鏈哄櫒浜篟OS缂栫▼锛堟敮鎸丆++鍜宲ython璇█锛�
   * - 2
     - :ref:`Kerloud Nano Indoor <kerloud_nano_indoor_option_zh>`
     -  Nvidia Jetson nano鏈鸿浇鐢佃剳锛屽厜娴佸畾浣�
     - 鏈変竴瀹氬熀纭€鐢ㄦ埛锛屽鍐呭簲鐢ㄦ垨鑰呮瘮璧涳紝鎺ヨЕNvidia娣卞害瀛︿範杞欢锛�
       杩涜鏈鸿浇ROS缂栫▼锛堟敮鎸丆++鍜宲ython璇█锛�
   * - 3
     - :ref:`Kerloud Nano VIO Indoor <kerloud_nano_vio_option_zh>`
     - Nvidia Jetson nano鏈鸿浇鐢佃剳, 瑙嗚閲岀▼璁★紙VIO锛夊畾浣�
     - 涓瓑鍩虹鐢ㄦ埛锛岄€傚悎瀹ゅ唴搴旂敤鎴栨瘮璧涳紝瑙嗚搴旂敤寮€鍙�
   * - 4
     - :ref:`Kerloud Optimus NX <kerloud_optimus_nx_option_zh>`
     - Nvidia Jetson NX (鍐呭瓨16GB) 鏈鸿浇鐢佃剳,
       瑙嗚閲岀▼璁★紙VIO锛夊畾浣嶏紝Ego-Planner閬块殰椋炶锛孲LAM寤哄浘
     - 楂樼骇鐢ㄦ埛锛岄€傚悎瀹ゅ唴搴旂敤鎴栨瘮璧涳紝SLAM搴旂敤鍜岃瑙夊簲鐢ㄥ紑鍙�
   * - 5
     - :ref:`Kerloud 600 Vision <kerloud600_vision_option_zh>`
     - Nvidia Jetson nano鏈鸿浇鐢佃剳, 瑙嗚閬块殰
     - 涓瓑鍩虹鐢ㄦ埛锛屽澶栨繁搴﹁瑙夐伩闅滅瓑鐩稿叧瑙嗚搴旂敤寮€鍙�
   * - 6
     - :ref:`Kerloud 600 Vision 4G <kerloud600_vision_4g_option_zh>`
     - Nvidia Jetson nano鏈鸿浇鐢佃剳, 瑙嗚閬块殰锛�4G杩滆窛椋炶
     - 涓瓑鍩虹鐢ㄦ埛锛屽澶栨繁搴﹁瑙夐伩闅滅瓑鐩稿叧瑙嗚搴旂敤寮€鍙戯紝4G瓒呰璺濋琛�
   * - 7
     - :ref:`Kerloud 600 Pro-Cam Pod <kerloud600_campod_option_zh>`
     - Nvidia Jetson nano鏈鸿浇鐢佃剳, 瑙嗚閬块殰锛岄珮娓呭悐鑸变簯鍙�
     - 楂樼骇鐢ㄦ埛锛岄潰鍚戝贰妫€瀹ゅ绛夎涓氬簲鐢紝鍋忓悜瑙嗚搴旂敤锛�
       杩涜鏈鸿浇鏈哄櫒浜篟OS杞欢缂栫▼锛堟敮鎸丆++鍜宲ython璇█锛夛紝搴旂敤鍖呮嫭绉诲姩骞冲彴闄嶈惤锛岃瑙夎拷韪瓑

.. toctree::
   :hidden:
   :maxdepth: 2

   kerloud300_options_zh.rst
   kerloud600_options_zh.rst