Displacement Correction of Hector SLAM Using ToF Sensor in Symmetric Corridor Environments

doi:10.22716/sckt.2026.14.1.005

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2026 Vol.14, Issue 1 Preview Page Next Page

Research Article

Displacement Correction of Hector SLAM Using ToF Sensor in Symmetric Corridor Environments 대칭 복도 환경에서 ToF 센서를 활용한 Hector SLAM 이동량 보정 방법: Sungbin Chong¹ and Sangrok Lee²
정성빈¹, 이상록²; ¹Student, Department of Electronic Engineering, Shinhan University
²Associate Professor, Department of Electronic Engineering, Shinhan University

¹신한대학교 전자공학과 학사과정, ²신한대학교 전자공학과 부교수

31 March 2026. pp. 45-52

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Abstract

2D LiDAR 기반의 Hector SLAM은 대칭적 복도 환경에서 특징점 매칭이 불안정해진다. 이에 따라 로봇이 전진해도 추정 위치가 변화하지 않는 전진 변위 퇴화 구간이 형성된다. 이러한 한계를 극복하기 위해 본 논문에서는 스텝 모터에 장착된 ToF 센서를 이용한 전진 변위 보정 기법을 제안한다. 제안한 방법은 ToF 센서를 일정 각도로 회전하면서 복도 내 구조물 모서리에서 발생하는 급격한 거리 변화를 검출하고, 해당 지점의 마지막 유효 코너 거리를 추출한 뒤 삼각함수 기반으로 로봇의 전진 변위를 계산한다. 계산된 전진 변위를 SLAM 좌표계에 반영하여 전진 변위 퇴화 구간의 위치를 보완한다. 실험 결과, 제안한 기법은 대칭적 복도 환경에서 전진 위치 갱신을 효과적으로 복원하였으며, 추가 센서나 복잡한 센서 융합 없이도 위치 추정 오차를 유의미하게 감소시킬 수 있음을 확인하였다.

2D LiDAR-based Hector SLAM often fails to update its pose in symmetric corridor environments due to unstable feature matching caused by repetitive geometric structures. Accordingly, the estimated forward displacement remains unchanged even when the robot continues to move, resulting in a forward displacement degeneracy region. To overcome this limitation, this study proposes a forward displacement correction method using a ToF sensor mounted on a stepper motor. The proposed method rotates the ToF sensor at a fixed angular interval, detects abrupt distance changes at corridor structure edges, extracts the last valid corner distance, and calculates the robot’s forward displacement based on trigonometric method. The calculated forward displacement is reflected in the SLAM coordinate frame to compensate for the pose in the displacement degeneracy region. Experimental results demonstrate that the proposed method effectively restores forward position updates in symmetric corridor environments and significantly reduces localization errors without requiring additional sensors or complex sensor fusion.

Keywords

Hector SLAM

Displacement correction

Indoor localization

2D LiDAR

ToF sensor

References

X. Yue, and M. He, “LiDAR-based SLAM for robotic mapping: state of the art and new frontiers”, arXiv:2311.00276, 2023.
G. Ge, Y. Zhang, Q. Jiang, and W. Wang, “Visual features assisted robot localization in symmetrical environment using laser SLAM”, Sensors, Vol. 21, No. 5, 1772, 2021.
10.3390/s21051772 33806414 PMC7961336
S. Kohlbrecher, J. Meyer, U. Klingauf, and O. Stryk, “A flexible and scalable SLAM system with full 3D motion estimation”, Proceedings of the IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 155-160, 2011.
10.1109/SSRR.2011.6106777
H. Lim, D. Kim, B. Kim, and H. Myung, “AdaLIO: Robust adaptive LiDAR-Inertial odometry in degenerate indoor environments,” Proceedings of the 20th International Conference on Ubiquitous Robots (UR), pp. 48-53, 2023.
10.1109/UR57808.2023.10202252
S. Saat, A. N. M. F. Airini, M. S. Saealal, A. R. Wan Norhisyam, and M. S. Farees Ezwan, “Hector SLAM 2D Mapping for Simultaneous Localization and Mapping (SLAM)”, Journal of Engineering and Applied Sciences, Vol. 14, No. 16, pp. 5610-5615, 2020.
10.36478/jeasci.2019.5610.5615
K. Ebadi, Y. Chang , M. Palieri, A. Stephens, A. Hatteland, E. Heiden, A. Thakur, N. Funabiki, B. Morrell, S. Wood, L. Carlone, and A.-A. Agha-Mohammadi, “LAMP: Large-Scale Autonomous Mapping and Positioning for exploration of perceptually-degraded subterranean environments”, arXiv:2003.01744, 2020.
10.1109/ICRA40945.2020.9197082
O. Jeongseok, and S. Gwibo, “Symmetrical Model Based SLAM (M-SLAM)”, Journal of Korean Institute of Intelligent Systems, Vol. 20, No. 4, pp. 463-468, 2010.
10.5391/JKIIS.2010.20.4.463
M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler, and A. Ng, “ROS: an open-source Robot Operating System”, ICRA Workshop, 2009.
T. Qin, P. Li, and S. Shen, “VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator”, IEEE Transactions on Robotics, Vol. 34, No. 4, pp. 1004-1020, 2018.
10.1109/TRO.2018.2853729
Slamtec, RPLIDAR A1 Development Kit Datasheet, Slamtec Co., Ltd., 2018. https://www.slamtec.com/en/Lidar/A1.
S. Foix, G. Alenya, and C. Torras, “Lock-in Time-of-Flight (ToF) Cameras: A Survey”, Sensors, Vol. 11, No. 2, pp. 1917-1936, 2011.
10.1109/JSEN.2010.2101060
STMicroelectronics, “VL53L1X Time-of-Flight Long Distance Ranging Sensor Datasheet”, STMicroelectronics, 2021.

Information

Publisher :The Society of Convergence Knowledge
Publisher(Ko) :융복합지식학회
Journal Title :The Society of Convergence Knowledge Transactions
Journal Title(Ko) :융복합지식학회논문지
Volume : 14
No :1
Pages :45-52
DOI :https://doi.org/10.22716/sckt.2026.14.1.005

[1] X. Yue, and M. He, “LiDAR-based SLAM for robotic mapping: state of the art and new frontiers”, arXiv:2311.00276, 2023.

[2] G. Ge, Y. Zhang, Q. Jiang, and W. Wang, “Visual features assisted robot localization in symmetrical environment using laser SLAM”, Sensors, Vol. 21, No. 5, 1772, 2021.
10.3390/s21051772 33806414 PMC7961336

[3] S. Kohlbrecher, J. Meyer, U. Klingauf, and O. Stryk, “A flexible and scalable SLAM system with full 3D motion estimation”, Proceedings of the IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 155-160, 2011.
10.1109/SSRR.2011.6106777

[4] H. Lim, D. Kim, B. Kim, and H. Myung, “AdaLIO: Robust adaptive LiDAR-Inertial odometry in degenerate indoor environments,” Proceedings of the 20th International Conference on Ubiquitous Robots (UR), pp. 48-53, 2023.
10.1109/UR57808.2023.10202252

[5] S. Saat, A. N. M. F. Airini, M. S. Saealal, A. R. Wan Norhisyam, and M. S. Farees Ezwan, “Hector SLAM 2D Mapping for Simultaneous Localization and Mapping (SLAM)”, Journal of Engineering and Applied Sciences, Vol. 14, No. 16, pp. 5610-5615, 2020.
10.36478/jeasci.2019.5610.5615

[6] K. Ebadi, Y. Chang , M. Palieri, A. Stephens, A. Hatteland, E. Heiden, A. Thakur, N. Funabiki, B. Morrell, S. Wood, L. Carlone, and A.-A. Agha-Mohammadi, “LAMP: Large-Scale Autonomous Mapping and Positioning for exploration of perceptually-degraded subterranean environments”, arXiv:2003.01744, 2020.
10.1109/ICRA40945.2020.9197082

[7] O. Jeongseok, and S. Gwibo, “Symmetrical Model Based SLAM (M-SLAM)”, Journal of Korean Institute of Intelligent Systems, Vol. 20, No. 4, pp. 463-468, 2010.
10.5391/JKIIS.2010.20.4.463

[8] M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler, and A. Ng, “ROS: an open-source Robot Operating System”, ICRA Workshop, 2009.

[9] T. Qin, P. Li, and S. Shen, “VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator”, IEEE Transactions on Robotics, Vol. 34, No. 4, pp. 1004-1020, 2018.
10.1109/TRO.2018.2853729

[10] Slamtec, RPLIDAR A1 Development Kit Datasheet, Slamtec Co., Ltd., 2018. https://www.slamtec.com/en/Lidar/A1.

[11] S. Foix, G. Alenya, and C. Torras, “Lock-in Time-of-Flight (ToF) Cameras: A Survey”, Sensors, Vol. 11, No. 2, pp. 1917-1936, 2011.
10.1109/JSEN.2010.2101060

[12] STMicroelectronics, “VL53L1X Time-of-Flight Long Distance Ranging Sensor Datasheet”, STMicroelectronics, 2021.

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