Human-Robot Collaborative SLAM-XR
Mohamad Karim Yassine, Malak Sayour, Adam Manasfi, Maya Hachach, Nadim Dib, Imad H. Elhajj, Boulos Asmar, Elie Khoury
Abstract
In this paper, we propose a collaborative centralized 3D mapping and localization framework that harnesses the capabilities of both SLAM (Simultaneous Localization And Mapping) and XR (eXtended Reality). On one hand, our framework allows for integrating local maps generated by a multitude of heterogeneous agents (e.g. robots) into a unified map. On the other hand, it allows human intervention at multiple levels: first, humans can inspect and intervene in the mapping process in situ to produce 3D maps, overlay virtual assets, and add annotations, all of which can contribute towards enhanced autonomy and navigation. Second, beyond the mapping aspect, a human can also intervene in the localization task of any collaborating robot by inspecting and correcting its generated paths, and, if necessary, enforcing a desired trajectory. Experiments inside two real settings demonstrated the superiority of the proposed system.
BibTeX
@inproceedings{iros2025_humanrobotcollab,
title = {Human-Robot Collaborative SLAM-XR},
author = {Mohamad Karim Yassine and Malak Sayour and Adam Manasfi and Maya Hachach and Nadim Dib and Imad H. Elhajj and Boulos Asmar and Elie Khoury and Daniel C. Asmar},
booktitle = {IROS 2025},
year = {2025}
}