Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916022999580672 |
|---|---|
| author | Djerroud, Halim Steyn, Nico Rabreau, Olivier Bonnin, Patrick Benali, Abderraouf |
| author_facet | Djerroud, Halim Steyn, Nico Rabreau, Olivier Bonnin, Patrick Benali, Abderraouf |
| contents | We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-D
cameras strategically throughout the workspace, UbiSLAM addresses limitations commonly encountered in traditional SLAM systems, such as sensitivity to
environmental changes and reliance on mobile unit sensors. This fixed-sensor approach enables real-time, comprehensive mapping, enhancing the localization
accuracy and responsiveness of robots operating within the environment. The centralized map generated by UbiSLAM is continuously updated, providing robots
with an accurate global view, which improves navigation, minimizes collisions, and facilitates smoother human-robot interactions in shared spaces. Beyond its
advantages, UbiSLAM faces challenges, particularly in ensuring complete spatial coverage and managing blind spots, which necessitate data integration from
the robots themselves. In this paper we discuss potential solutions, such as automatic calibration for optimal camera placement and orientation, along with
enhanced communication protocols for real-time data sharing. The proposed model reduces the computational load on individual robotic units, allowing less
complex robotic platforms to operate effectively while enhancing the robustness of the overall system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_18385 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments Djerroud, Halim Steyn, Nico Rabreau, Olivier Bonnin, Patrick Benali, Abderraouf Robotics Artificial Intelligence 68T40, 68T45, 93E11, 90C10 I.2.9; I.2.10; I.4.8 We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-D cameras strategically throughout the workspace, UbiSLAM addresses limitations commonly encountered in traditional SLAM systems, such as sensitivity to environmental changes and reliance on mobile unit sensors. This fixed-sensor approach enables real-time, comprehensive mapping, enhancing the localization accuracy and responsiveness of robots operating within the environment. The centralized map generated by UbiSLAM is continuously updated, providing robots with an accurate global view, which improves navigation, minimizes collisions, and facilitates smoother human-robot interactions in shared spaces. Beyond its advantages, UbiSLAM faces challenges, particularly in ensuring complete spatial coverage and managing blind spots, which necessitate data integration from the robots themselves. In this paper we discuss potential solutions, such as automatic calibration for optimal camera placement and orientation, along with enhanced communication protocols for real-time data sharing. The proposed model reduces the computational load on individual robotic units, allowing less complex robotic platforms to operate effectively while enhancing the robustness of the overall system. |
| title | Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments |
| topic | Robotics Artificial Intelligence 68T40, 68T45, 93E11, 90C10 I.2.9; I.2.10; I.4.8 |
| url | https://arxiv.org/abs/2605.18385 |