single-rb.php

JRM Vol.37 No.4 pp. 815-824
doi: 10.20965/jrm.2025.p0815
(2025)

Paper:

Vision/INS/Altimeter-Based Navigation and Control for Autonomous Drones in Indoor Environments

Satoshi Suzuki ORCID Icon

Chiba University
1-33 Yayoi-cho, Inage-ku, Chiba, Chiba 263-8522, Japan

Received:
September 2, 2024
Accepted:
May 28, 2025
Published:
August 20, 2025
Keywords:
drone, monocular-SLAM, altimeter, EKF, indoor navigation
Abstract

In this study, we aim to develop a navigation and control system that enables drones to fly autonomously with high accuracy in indoor environments, including narrow aisles. First, we propose an EKF-based vision-aided inertial navigation system with altimeter (VINS-ALT), which combines monocular-SLAM results with data from the IMU and altimeter. In addition, a detection and correction system is designed to reduce altimeter errors caused by changes in ground surface characteristics, such as steps and slopes. Furthermore, a flight control system that achieves both trajectory tracking performance and robustness is developed. Finally, the effectiveness of the entire system is validated through autonomous flight control experiments in an indoor environment.

Indoor autonomous flying drone

Indoor autonomous flying drone

Cite this article as:
S. Suzuki, “Vision/INS/Altimeter-Based Navigation and Control for Autonomous Drones in Indoor Environments,” J. Robot. Mechatron., Vol.37 No.4, pp. 815-824, 2025.
Data files:
References
  1. [1] A. M. Atieh, H. Kaylani, Y. Al-abdallat, A. Qaderi, L. Ghoul, L. Jaradat, and I. Hdairis, “Performance Improvement of Inventory Management System Processes by an Automated Warehouse Management System,” Procedia CIRP, Vol.41, pp. 568-572, 2016. https://doi.org/10.1016/j.procir.2015.12.122
  2. [2] J. Tiemann and C. Wietfeld, “Scalable and Precise Multi-UAV Indoor Navigation Using TDOA-based UWB Localization,” 2017 Int. Conf. on Indoor Positioning and Indoor Navigation, 2017. https://doi.org/10.1109/IPIN.2017.8115937
  3. [3] J. Tiemann, F. Schweikowski, and C. Wietfeld, “Design of an UWB Indoor-Positioning System for UAV Navigation in GNSS-Denied Environments,” 2015 Int. Conf. on Indoor Positioning and Indoor Navigation, 2015. https://doi.org/10.1109/IPIN.2015.7346960
  4. [4] J. Song, Z. Liu, X. Liu, and J. Guo, “Tightly Coupled Visual Inertial Odometry based on Artificial Landmarks,” 2018 IEEE Int. Conf. on Information and Automation, 2018. https://doi.org/10.1109/ICInfA.2018.8812447
  5. [5] X. Zhang, Y. Du, F. Chen, L. Qin, and Q. Ling, “Indoor Position Control of a Quadrotor UAV with Monocular Vision Feedback,” 37th Chinese Control Conf., 2018. https://doi.org/10.23919/ChiCC.2018.8483542
  6. [6] J. Yang, Y. Li, L. Cao, Y. Jiang, L. Sun, and Q. Xie, “A Survey of SLAM Research based on LiDAR Sensors,” Int. J. Sens., Vol.1, No.1, Article No.1003, 2019.
  7. [7] S. Hara, T. Shimizu, M. Konishi, R. Yamamura, and S. Ikemoto, “Autonomous Mobile Robot for Outdoor Slope Using 2D LiDAR with Uniaxial Gimbal Mechanism,” J. Robot. Mechatron., Vol.32, No.6, pp. 1173-1182, 2020. https://doi.org/10.20965/jrm.2020.p1173
  8. [8] M. Inagawa, K. Yoshizawa, T. Kawabe, and T. Takei, “Automatic Calibration of Environmentally Installed 3D-LiDAR Group Used for Localization of Construction Vehicles,” J. Robot. Mechatron., Vol.36, No.2, pp. 320-333, 2024. https://doi.org/10.20965/jrm.2024.p0320
  9. [9] T. Taketomi, H. Uchiyama, and S. Ikeda, “Visual-SLAM algorithms: A survey from 2010 to 2016,” IPSJ Trans. on Computer Vision and Applications, Vol.9, Article No.16, 2017. https://doi.org/10.1186/s41074-017-0027-2
  10. [10] L. Sun, R. P. Singh, and F. Kanehiro, “Visual SLAM Framework Based on Segmentation with the Improvement of Loop Closure Detection in Dynamic Environments,” J. Robot. Mechatron., Vol.33, No.6, pp. 1385-1397, 2021. https://doi.org/10.20965/jrm.2021.p1385
  11. [11] Z. Chai and T. Matsumaru, “ORB-SHOT SLAM: Trajectory Correction by 3D Loop Closing Based on Bag-of-Visual-Words (BoVW) Model for RGB-D Visual SLAM,” J. Robot. Mechatron., Vol.29, No.2, pp. 365-380, 2017. https://doi.org/10.20965/jrm.2017.p0365
  12. [12] T. Suzuki, Y. Amano, T. Hashizume, and S. Suzuki, “3D Terrain Reconstruction by Small Unmanned Aerial Vehicle Using SIFT-Based Monocular SLAM,” J. Robot. Mechatron., Vol.23, No.2, pp. 292-301, 2011. https://doi.org/10.20965/jrm.2011.p0292
  13. [13] S. Weiss and R. Siegwart, “Real-time metric state estimation for modular vision-inertial systems,” 2011 IEEE Int. Conf. on Robotics and Automation, pp. 4531-4537, 2011. https://doi.org/10.1109/ICRA.2011.5979982
  14. [14] T. Qin, P. Li, and S. Shen, “VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator,” IEEE Trans. on Robotics, Vol.34, No.4, pp. 1004-1020, 2018. https://doi.org/10.1109/TRO.2018.2853729
  15. [15] C. Campos, R. Elvira, J. J. G. Rodríguez, J. M. M. Montiel, and J. D. Tardós, “ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM,” IEEE Trans. on Robotics, Vol.37, No.6, pp. 1874-1890, 2021. https://doi.org/10.1109/TRO.2021.3075644
  16. [16] K. Fodor and R. Viktor, “Validation of ORB-SLAM3 and VINS-Mono with Low-Cost Sensor Setup in Outdoor Environment,” 2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI), pp. 000027-000032, 2023. https://doi.org/10.1109/SAMI58000.2023.10044540
  17. [17] A. M. Barros, M. Michel, Y. Moline, G. Corre, and F. Carrel, “A Comprehensive Survey of Visual SLAM Algorithms,” Robotics, Vol.11, No.1, Article No.24 2022. https://doi.org/10.3390/robotics11010024
  18. [18] E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, “ORB: An efficient alternative to SIFT or SURF,” 2011 Int. on Computer Vision, 2011. https://doi.org/10.1109/ICCV.2011.6126544
  19. [19] Q. Li, R. Li, K. Ji, and W. Dai, “Kalman Filter and Its Application,” 2015 8th Int. Conf. on Intelligent Networks and Intelligent Systems (ICINIS), pp. 74-77, 2015. https://doi.org/10.1109/ICINIS.2015.35
  20. [20] S. Hochreiter and J. Schmidhuber, “Long Short-Term Memory,” Neural Comput., Vol.9, No.8, pp. 1735-1780, 1997. https://doi.org/10.1162/neco.1997.9.8.1735

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Aug. 19, 2025