Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots

This paper proposes an approach to enhance the robustness and accuracy of visual simultaneous localization and mapping (SLAM) for ground wheeled mobile robots in dynamic environments. The proposed method incorporates encoder measurements to establish optimization constraints in bundle adjustment. To...

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Main Authors: Andrey Penkovskiy, Jaafar Mahmoud
Format: Article
Language:English
Published: FRUCT 2023-05-01
Series:Proceedings of the XXth Conference of Open Innovations Association FRUCT
Subjects:
Online Access:https://www.fruct.org/publications/volume-33/fruct33/files/Mah.pdf
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author Andrey Penkovskiy
Jaafar Mahmoud
author_facet Andrey Penkovskiy
Jaafar Mahmoud
author_sort Andrey Penkovskiy
collection DOAJ
description This paper proposes an approach to enhance the robustness and accuracy of visual simultaneous localization and mapping (SLAM) for ground wheeled mobile robots in dynamic environments. The proposed method incorporates encoder measurements to establish optimization constraints in bundle adjustment. To further improve robustness, a geometric technique utilizing KMeans clustering with epipolar constraints and the SegNet for semantic segmentation is employed to filter out features detected on moving objects. These modifications are integrated into the state-of-the-art SLAM system ORB-SLAM3 and demonstrate superior accuracy and real-time performance compared to the baseline approach. The effectiveness of the proposed method is demonstrated through multiple OpenLoris and IROS Lifelong SLAM competition scenarios.
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spelling doaj.art-e6518c4e76534358b4489e3ea3000e7f2023-06-09T11:41:51ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372023-05-0133118519110.23919/FRUCT58615.2023.10143050Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled RobotsAndrey Penkovskiy0Jaafar Mahmoud1ITMO UniversityITMO UniversityThis paper proposes an approach to enhance the robustness and accuracy of visual simultaneous localization and mapping (SLAM) for ground wheeled mobile robots in dynamic environments. The proposed method incorporates encoder measurements to establish optimization constraints in bundle adjustment. To further improve robustness, a geometric technique utilizing KMeans clustering with epipolar constraints and the SegNet for semantic segmentation is employed to filter out features detected on moving objects. These modifications are integrated into the state-of-the-art SLAM system ORB-SLAM3 and demonstrate superior accuracy and real-time performance compared to the baseline approach. The effectiveness of the proposed method is demonstrated through multiple OpenLoris and IROS Lifelong SLAM competition scenarios.https://www.fruct.org/publications/volume-33/fruct33/files/Mah.pdfslammobile robotsdynamic environmentsoptimization
spellingShingle Andrey Penkovskiy
Jaafar Mahmoud
Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
Proceedings of the XXth Conference of Open Innovations Association FRUCT
slam
mobile robots
dynamic environments
optimization
title Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
title_full Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
title_fullStr Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
title_full_unstemmed Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
title_short Dynamic Environments and Robust SLAM: Optimizing Sensor Fusion and Semantics for Wheeled Robots
title_sort dynamic environments and robust slam optimizing sensor fusion and semantics for wheeled robots
topic slam
mobile robots
dynamic environments
optimization
url https://www.fruct.org/publications/volume-33/fruct33/files/Mah.pdf
work_keys_str_mv AT andreypenkovskiy dynamicenvironmentsandrobustslamoptimizingsensorfusionandsemanticsforwheeledrobots
AT jaafarmahmoud dynamicenvironmentsandrobustslamoptimizingsensorfusionandsemanticsforwheeledrobots