["研究人員從斯坦福大學提出了一種名爲 Mobile ALOHA 的低成本整體遠程操作系統，用於收集關於整體遠程操作的數據。","Mobile ALOHA 通過將其放在輪式底座上，擴展了原始 ALOHA 的功能，使其具有移動能力。","研究人員使用靜態 ALOHA 數據集進行模仿學習，通過預訓練和聯合訓練，在移動操作任務中取得了良好的性能。","該研究爲日常需要整體遠程操作的任務提供了一種低成本、高效的數據收集方法。"]
專注於隱私和安全的網絡瀏覽器
lerobot
動作分塊變換器策略，針對AlohaInsertion環境訓練，用於精細的雙臂操作任務。
動作分塊變換器策略，專為AlohaTransferCube環境設計，用於精細的雙手機械臂操作任務
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