对比三种教机器人方式，发现用手动引导最省力且高效
How Should We Teach Robots? A Comparison of Kinesthetic, Joystick, and Gesture-Based Teaching
- 用身体带动机器人教学，比遥控或手势更省力
- 手动教学在需要精准角度和接触的任务中成功率最高
- 手势教学虽不稳，但部分场景表现接近手动引导
通过八名参与者在三项操作任务中的用户研究，比较了手动引导、摇杆遥控和手势教学三种机器人教学方式。评估指标包括重放成功率、改进版NASA-TLX工作负荷评分及常见教学错误。手动引导在需精确方向控制和接触的任务中表现最优，演示时长最短，工作负荷最低，成功率最高；摇杆遥控在简单插销任务中表现最佳；手势教学整体可靠性较低，但在某些情况下表现优于预期，甚至可媲美手动引导。
原文摘要 · Abstract (English)
Instructing robots from demonstrations can be done through different teaching modalities, each with different usability and performance trade-offs. This paper compares kinesthetic guidance, joystick teleoperation, and hand gestures in a user study with eight participants. We evaluate replay success, modified NASA-TLX workload, and common teaching errors across three manipulation tasks. Kinesthetic guidance produced the shortest demonstrations, lowest workload, and highest success on the more orientation-sensitive and contact-rich tasks. Joystick teleoperation performed best on simple peg picking. Hand-gesture teaching, although less reliable overall, performed better than expected and in some cases achieved results comparable to kinesthetic guidance.
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