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arXiv 2409.15464cs.ROcs.HC
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迈向具有双虚拟空间的预测性扩展现实遥操作系统

Toward a Predictive eXtended Reality Teleoperation System with Duo-Virtual Spaces

University of California, Riverside(加州大学河滨分校)

Ziliang Zhang, Cong Liu, Hyoseung Kim

AI总结:

本文针对扩展现实遥操作中因大延迟导致快速精确任务失败的问题,提出一种双虚拟空间设计,通过在用户侧本地化智能体和物体并周期性校准真实位姿来优化端到端延迟。

摘要:

扩展现实(XR)相比传统2D控制为遥操作机器人提供了更直观的交互方式。近期研究为基于XR的可用遥操作奠定了基础,但由于用户运动与智能体反馈之间存在较大延迟,它在需要快速运动和精确操作的任务中会失败。在这项工作中,我们分析了一个最先进的XR遥操作系统中的端到端延迟,并提出了通过实现双虚拟空间设计来优化延迟的想法,即在用户侧虚拟空间中本地化智能体和物体,同时利用来自智能体侧虚拟空间的周期性真实位姿进行校准。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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