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Symmetry
Volume 18
Issue 5
10.3390/sym18050876
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study

by
Raghad Hadi Hasan
1,
Athraa Hashim Mohammed
2,
Faten Mezher Radhi
3 and
Bashar Alsadik
4,*
1
Department of Surveying, College of Engineering, University of Baghdad, Baghdad 10071, Iraq
2
Department of Civil Engineering, College of Engineering, University of Baghdad, Baghdad 10071, Iraq
3
Construction and Building Department, Technical College AI Mussaib, AI Furat AI Awsat Technical University, Najaf 54001, Iraq
4
ITC Faculty, University of Twente, 7522 NB Enschede, The Netherlands
*
Author to whom correspondence should be addressed.
Symmetry 2026, 18(5), 876; https://doi.org/10.3390/sym18050876 (registering DOI)
Submission received: 20 April 2026 / Revised: 18 May 2026 / Accepted: 19 May 2026 / Published: 21 May 2026
(This article belongs to the Special Issue Asymmetric and Symmetric in Deep Computer Vision and Generative Modeling)
Versions Notes

Abstract

The configuration of a multi-LiDAR system impacts coverage, redundancy, and observability in mobile mapping. In this study, a multi-LiDAR configuration is modeled as a constrained optimization problem that considers symmetry and clearance constraints. A physics-based simulation is applied to evaluate coverage, overlap, and angular diversity for spinning LiDARs such as the Ouster OS1-64 and the Velodyne VLP-16. Three methods of Bayesian Optimization (BO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are used. In an indoor space, all methods find symmetric multi-sensor configurations that maximize coverage and redundancy. GA and PSO methods required thousands of evaluations, whereas BO demonstrated excellent efficiency by converging in fewer iterations. Validation using simulated, realistic trajectories and ground-truth environments shows that symmetric multi-LiDAR configuration increases surface completeness by 10–11% over single-sensor setups (up to 27% for OS1-64 and 42% for VLP-16). The results further show that bilateral symmetry is a practical mounting constraint and also a robust design principle that improves mapping completeness.
Keywords: multi-LiDAR optimization; Bayesian optimization; genetic algorithms; particle swarm optimization; LiDAR mount configuration multi-LiDAR optimization; Bayesian optimization; genetic algorithms; particle swarm optimization; LiDAR mount configuration

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MDPI and ACS Style

Hasan, R.H.; Mohammed, A.H.; Radhi, F.M.; Alsadik, B. Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study. Symmetry 2026, 18, 876. https://doi.org/10.3390/sym18050876

AMA Style

Hasan RH, Mohammed AH, Radhi FM, Alsadik B. Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study. Symmetry. 2026; 18(5):876. https://doi.org/10.3390/sym18050876

Chicago/Turabian Style

Hasan, Raghad Hadi, Athraa Hashim Mohammed, Faten Mezher Radhi, and Bashar Alsadik. 2026. "Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study" Symmetry 18, no. 5: 876. https://doi.org/10.3390/sym18050876

APA Style

Hasan, R. H., Mohammed, A. H., Radhi, F. M., & Alsadik, B. (2026). Mixed Discrete–Continuous Constrained Optimization of Symmetric Multi-LiDAR Mount Configurations for Mapping Systems: A Physics-Based Simulation Study. Symmetry, 18(5), 876. https://doi.org/10.3390/sym18050876

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