Probabilistic occupancy grid for radio-based SLAM
Li, Xuhong LU ; Leitinger, Erik ; Tufvesson, Fredrik LU
and Meyer, Florian
(2026)
- Abstract
- Sensing is an integral part of 6G and beyond systems, providing exceptional environmental perception along with communication. Radio frequency (RF)–based sensing often relies on simplified geometric assumptions (e.g., point scatterers or planar surfaces) to model specular multipath and keep inference tractable. However, such representations are not physically informative and fail to accurately capture extended objects with complex shapes and properties. This paper presents a probabilistic occupancy grid framework for radio-based simultaneous localization and mapping (SLAM), jointly reconstructing geometric structures and their radio-related properties. The proposed occupancy grid map representation is integrated into a multipath-based SLAM... (More)
- Sensing is an integral part of 6G and beyond systems, providing exceptional environmental perception along with communication. Radio frequency (RF)–based sensing often relies on simplified geometric assumptions (e.g., point scatterers or planar surfaces) to model specular multipath and keep inference tractable. However, such representations are not physically informative and fail to accurately capture extended objects with complex shapes and properties. This paper presents a probabilistic occupancy grid framework for radio-based simultaneous localization and mapping (SLAM), jointly reconstructing geometric structures and their radio-related properties. The proposed occupancy grid map representation is integrated into a multipath-based SLAM (MP-SLAM) formulation to enable simultaneous mobile-agent localization and environment mapping using multipath measurements.
To connect RF measurements with the grid map, a surface model is employed to describe candidate reflection paths, while occupancy grid cell states capture measurement uncertainties and fine–grained geometric details. Object RF–related properties are modeled via reflection coefficients. The proposed framework offers a principled, proof-of-concept approach to physically interpretable radio-based mapping, and simulation results demonstrate accurate reconstruction of geometry and material properties, as well as high-accuracy localization. In addition, the results highlight the potential to use prior occupancy maps obtained from other radio devices or complementary sensors for subsequent map extension and refinement. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/70aeb1a8-bf65-4c99-8a9f-0ea240a81493
- author
- Li, Xuhong
LU
; Leitinger, Erik
; Tufvesson, Fredrik
LU
and Meyer, Florian
- organization
- publishing date
- 2026
- type
- Working paper/Preprint
- publication status
- published
- subject
- pages
- 8 pages
- language
- English
- LU publication?
- yes
- id
- 70aeb1a8-bf65-4c99-8a9f-0ea240a81493
- alternative location
- http://arxiv.org/abs/2603.03559
- date added to LUP
- 2026-03-05 10:21:40
- date last changed
- 2026-03-31 10:11:06
@misc{70aeb1a8-bf65-4c99-8a9f-0ea240a81493,
abstract = {{Sensing is an integral part of 6G and beyond systems, providing exceptional environmental perception along with communication. Radio frequency (RF)–based sensing often relies on simplified geometric assumptions (e.g., point scatterers or planar surfaces) to model specular multipath and keep inference tractable. However, such representations are not physically informative and fail to accurately capture extended objects with complex shapes and properties. This paper presents a probabilistic occupancy grid framework for radio-based simultaneous localization and mapping (SLAM), jointly reconstructing geometric structures and their radio-related properties. The proposed occupancy grid map representation is integrated into a multipath-based SLAM (MP-SLAM) formulation to enable simultaneous mobile-agent localization and environment mapping using multipath measurements.<br/><br/>To connect RF measurements with the grid map, a surface model is employed to describe candidate reflection paths, while occupancy grid cell states capture measurement uncertainties and fine–grained geometric details. Object RF–related properties are modeled via reflection coefficients. The proposed framework offers a principled, proof-of-concept approach to physically interpretable radio-based mapping, and simulation results demonstrate accurate reconstruction of geometry and material properties, as well as high-accuracy localization. In addition, the results highlight the potential to use prior occupancy maps obtained from other radio devices or complementary sensors for subsequent map extension and refinement.}},
author = {{Li, Xuhong and Leitinger, Erik and Tufvesson, Fredrik and Meyer, Florian}},
language = {{eng}},
note = {{Preprint}},
title = {{Probabilistic occupancy grid for radio-based SLAM}},
url = {{http://arxiv.org/abs/2603.03559}},
year = {{2026}},
}