降低XR遥操作延迟，提升远程机器人操控的实时性与精度。
Toward a Predictive eXtended Reality Teleoperation System with Duo-Virtual Spaces
- 构建双虚拟空间架构，将机器人与物体本地化在用户端空间。
- 通过周期性接收真实位姿校准，实现高精度同步。
- 适用于需要快速动作和精准操作的远程控制场景。
扩展现实（XR）相比传统2D控制提供了更直观的机器人遥操作交互方式。尽管近期研究已奠定可用的XR遥操作基础，但在要求快速运动与精确操作的任务中仍因用户动作与代理反馈间的显著延迟而表现不佳。本文分析了当前先进XR遥操作系统的端到端延迟，并提出通过双虚拟空间设计优化延迟：将代理及物体本地化于用户端虚拟空间，同时定期从代理端虚拟空间获取真实位姿进行校准。该方法有效缓解了延迟问题，提升了系统响应性与操作精度。
原文摘要 · Abstract (English)
Extended Reality (XR) provides a more intuitive interaction method for teleoperating robots compared to traditional 2D controls. Recent studies have laid the groundwork for usable teleoperation with XR, but it fails in tasks requiring rapid motion and precise manipulations due to the large delay between user motion and agent feedback. In this work, we profile the end-to-end latency in a state-of-the-art XR teleoperation system and propose our idea to optimize the latency by implementing a duo-virtual spaces design and localizing the agent and objects in the user-side virtual space, while calibrating with periodic ground-truth poses from the agent-side virtual space.
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