对比VR与SpaceMouse在动静态任务中表现，发现VR更优且适合动态控制。
Static Is Not Enough: A Comparative Study of VR and SpaceMouse in Static and Dynamic Teleoperation Tasks
- 在动静态任务中对比VR控制器与SpaceMouse性能
- VR成功率更高，执行更快，工作负荷更低
- 结果适用于动态遥操作场景，开源接口已发布
模仿学习依赖高质量示范数据，而遥操作是获取这些数据的主要方式，因此遥操作接口的选择至关重要。以往研究多关注静态任务（即离散、分段动作），但示范数据也包含需要反应式控制的动态任务。由于动态任务对界面需求本质不同，静态任务的结论无法推广。为此，我们开展一项被试内实验，比较了虚拟现实（VR）控制器与SpaceMouse在两个静态任务和两个动态任务中的表现（$N=25$）。评估指标包括成功率、任务时长、累计成功次数，以及NASA-TLX、SUS问卷和开放反馈。结果显示，VR在统计上显著占优：在动态任务中成功率更高，各类任务成功执行时间更短，首次成功尝试更早，且工作负荷更低、可用性更高。鉴于现有VR遥操作系统极少开源或适配动态任务，我们公开了本研究中的VR接口以填补这一空白。
原文摘要 · Abstract (English)
Imitation learning relies on high-quality demonstrations, and teleoperation is a primary way to collect them, making teleoperation interface choice crucial for the data. Prior work mainly focused on static tasks, i.e., discrete, segmented motions, yet demonstrations also include dynamic tasks requiring reactive control. As dynamic tasks impose fundamentally different interface demands, insights from static-task evaluations cannot generalize. To address this gap, we conduct a within-subjects study comparing a VR controller and a SpaceMouse across two static and two dynamic tasks ($N=25$). We assess success rate, task duration, cumulative success, alongside NASA-TLX, SUS, and open-ended feedback. Results show statistically significant advantages for VR: higher success rates, particularly on dynamic tasks, shorter successful execution times across tasks, and earlier successes across attempts, with significantly lower workload and higher usability. As existing VR teleoperation systems are rarely open-source or suited for dynamic tasks, we release our VR interface to fill this gap.
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