Comparative benchmarking of 2d lidar slam algorithms with ros 2 on raspberry pi 5

Basit Öğe Kaydı
dc.authorid0009-0006-7043-5669
dc.authorid0000-0003-0261-4404
dc.contributor.authorŞahin, Ulaş
dc.contributor.authorCan, Göktürk
dc.contributor.authorAltıok, Ezgi
dc.contributor.authorÇavdar, İbrahim
dc.contributor.authorGözüaçık, Necip
dc.date.accessioned2026-04-29T12:08:57Z
dc.date.available2026-04-29T12:08:57Z
dc.date.issued2026
dc.departmentFakülteler, Eczacılık Fakültesi, Eczacılık Meslek Bilimleri Bölümü, Farmakognozi Ana Bilim Dalı
dc.description.abstractMobile robotics increasingly relies on SLAM for robust autonomous navigation. While many algorithms exist, systematic comparisons within the ROS 2 framework under real-world conditions remain limited. This study addresses this gap by benchmarking three widely used 2D LiDAR-based methods—GMapping, Hector SLAM, and Cartographer—on a wheeled mobile robot. Using both simulation and on-device experiments, we evaluate mapping accuracy, localization quality, and computational efficiency. Results show that Cartographer achieves the highest accuracy in structured environments, Hector SLAM demonstrates robustness without odometry, and GMapping performs reliably only in small-scale settings. These findings highlight trade-offs relevant to embedded deployment. The main contributions are: (i) a reproducible evaluation pipeline on ROS 2, (ii) quantitative analysis of accuracy versus resource usage on Raspberry Pi 5, and (iii) practical guidelines for algorithm selection in autonomous systems. This work advances the understanding of ROS 2-based SLAM and supports informed deployment in robotics applications.
dc.identifier.citationŞahin, U., Can, G., Altıok, E., Çavdar, İ., & Gözüaçık, N. (2026). Comparative benchmarking of 2d lidar slam algorithms with ros 2 on raspberry pi 5. 2026 12th International Conference on Automation, Robotics, and Applications, pp. 117-122. https://doi.org/10.1109/ICARA69401.2026.11480335
dc.identifier.doi10.1109/ICARA69401.2026.11480335
dc.identifier.endpage122
dc.identifier.issn2767-7745
dc.identifier.issn2767-7737
dc.identifier.startpage117
dc.identifier.urihttps://doi.org/10.1109/ICARA69401.2026.11480335
dc.identifier.urihttps://hdl.handle.net/20.500.13055/1451
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorŞahin, Ulaş
dc.institutionauthorCan, Göktürk
dc.institutionauthorAltıok, Ezgi
dc.institutionauthorÇavdar, İbrahim
dc.institutionauthorGözüaçık, Necip
dc.institutionauthorid0009-0006-7043-5669
dc.institutionauthorid0000-0003-0261-4404
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2026 12th International Conference on Automation, Robotics, and Applications
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAutonomous Navigation
dc.subjectROS 2
dc.subjectLidar-Based SLAM
dc.subjectEmbedded Robotics
dc.subjectExperimental Evaluation
dc.subjectPerformance Benchmarking
dc.titleComparative benchmarking of 2d lidar slam algorithms with ros 2 on raspberry pi 5
dc.typeConference Object
dspace.entity.typePublication

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