强大的协作视觉惯性SLAM用于移动增强现实
IEEE transactions on visualization and computer graphics
|September 9, 2024
概括
本研究介绍了一个强大的协作多代理视觉惯性同时定位和映射 (VI-SLAM) 系统,用于移动增强现实 (AR). 它通过合并来自多个设备的子地图来提高跟踪精度和系统稳定性,以实现一致的全球映射.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 增强现实是一种增强现实.
背景情况:
- 实时本地化和稳定性是多用户移动AR的关键挑战.
- 轻量级设备需要协作信息来提高跟踪精度和系统弹性.
研究的目的:
- 为移动AR提出一个强大的集中式协作多代理VI-SLAM系统.
- 为了实现高效,一致的服务器端映射和移动设备上的实时跟踪.
主要方法:
- 一个轻量级的视觉惯性计数 (VIO) 前端在移动设备上用于跟踪.
- 一个远程服务器后台,用于更新多个子地图和执行子地图合并.
- 一个基于互联网可见性领域的地图注册和融合战略,以实现在线一致性.
主要成果:
- 该系统通过重叠区域的子地图融合实现了全球一致的映射.
- 通过将全球地图更新到本地地图,可以提高前端跟踪的准确性.
- 紧密结合的策略确保了多代理前端阵地估计的一致性.
结论:
- 拟议的VI-SLAM系统有效地提高了多用户移动AR的本地化准确性和稳定性.
- 该系统展示了高效的服务器端映射和可扩展的AR应用程序的部署.
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