仅用一次示范，双臂机器人即可精准完成复杂协作任务。
One-Shot Dual-Arm Imitation Learning
- 三阶段视觉伺服实现末端与目标的精准对齐
- 单次示范后无需额外训练即可完成六项任务
- 适用于真实场景中的干扰和遮挡，适合工业协作应用
我们提出了一种单次示范双臂模仿学习方法（ODIL），使双臂机器人仅需一次任务示范即可学会精确且协调的日常操作。ODIL采用新型三阶段视觉伺服（3-VS）方法，在末端执行器与目标物体间实现精准对齐，随后重放示范轨迹即可完成任务。该方法无需预先的任务或物体知识，也无需示范后的额外数据收集与训练。此外，我们提出一种新双臂协调范式，支持从单一示范中学习双臂协作任务。ODIL在真实双臂机器人上测试，于4-DoF与6-DoF设置下均在六项高精度协作任务中达到领先性能，并在存在干扰物和部分遮挡时表现出鲁棒性。视频展示见：https://www.robot-learning.uk/one-shot-dual-arm。
原文摘要 · Abstract (English)
We introduce One-Shot Dual-Arm Imitation Learning (ODIL), which enables dual-arm robots to learn precise and coordinated everyday tasks from just a single demonstration of the task. ODIL uses a new three-stage visual servoing (3-VS) method for precise alignment between the end-effector and target object, after which replay of the demonstration trajectory is sufficient to perform the task. This is achieved without requiring prior task or object knowledge, or additional data collection and training following the single demonstration. Furthermore, we propose a new dual-arm coordination paradigm for learning dual-arm tasks from a single demonstration. ODIL was tested on a real-world dual-arm robot, demonstrating state-of-the-art performance across six precise and coordinated tasks in both 4-DoF and 6-DoF settings, and showing robustness in the presence of distractor objects and partial occlusions. Videos are available at: https://www.robot-learning.uk/one-shot-dual-arm.
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