Have a personal or library account? Click to login

Heterogeneous Map Fusion from Occupancy Grid Histograms for Mobile Robots

Open Access
|Aug 2024

References

  1. H. Bavle, J. L. Sanchez-Lopez, C. Cimarelli, A. Tourani, and H. Voos, “From slam to situational awareness: Challenges and survey,” Sensors, vol. 23, no.10, May 2023, Art. no. 4849. https://doi.org/10.3390/s23104849
  2. L. P. Nalla Perumal and A. S. Arockia Doss, “Sensor fusion for automotive dead reckoning using GPS and IMU for accurate position and velocity estimation,” Trends in Mechanical and Biomedical Design: Select Proceedings of ICMechD 2019, pp. 83–95, 2021. https://doi.org/10.1007/978-981-15-4488-0_8
  3. N. El-Sheimy and Y. Li, “Indoor navigation: State of the art and future trends,” Satellite Navigation, vol. 2, no. 1, May 2021, Art. no. 7. https://doi.org/10.1186/s43020-021-00041-3
  4. I. A. Kazerouni, L. Fitzgerald, G. Dooly, and D. Toal, “A survey of state-of-the-art on visual slam,” Expert Systems with Applications, vol. 205, Nov. 2022, Art. no. 117734. https://doi.org/10.1016/j.eswa.2022.117734
  5. M. Bujanca, X. Shi, M. Spear, P. Zhao, B. Lennox, and M. Luján, “Robust slam systems: Are we there yet?” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, Sep. 2021, pp. 5320–5327. https://doi.org/10.1109/IROS51168.2021.9636814
  6. W. Chen, C. Zhou, G. Shang, X. Wang, Z. Li, C. Xu, and K. Hu, “Slam overview: From single sensor to heterogeneous fusion,” Remote Sensing, vol. 14, no. 23, Nov. 2022, Art. no. 6033. https://doi.org/10.3390/rs14236033
  7. C. V. Jones, G. E. Hall, S. J. Baron, B. Hild, S. Zickler, and J. Sinnigen, “Mobile cleaning robot artificial intelligence for situational awareness,” U.S. Patent 10 878 294, Dec. 29, 2020.
  8. M. Munich, A. Kolling, M. Narayana, and P. Fong, “Mapping for autonomous mobile robots,” U.S. Patent 11 249 482, Feb. 15, 2022.
  9. C. A. Velásquez Hernández and F. A. Prieto Ortiz, “A real-time map merging strategy for robust collaborative reconstruction of unknown environments,” Expert Systems with Applications, vol. 145, May 2020, Art. no. 113109. https://doi.org/10.1016/j.eswa.2019.113109
  10. Y. Xie, Y. Tang, R. Zhou, Y. Guo, and H. Shi, “Map merging with terrain-adaptive density using mobile 3D laser scanner,” Robotics and Autonomous Systems, vol. 134, Dec. 2020, Art. no. 103649. https://doi.org/10.1016/j.robot.2020.103649
  11. Z. Li, B. Xu, D. Wu, K. Zhao, S. Chen, M. Lu, and J. Cong, “A YOLOGGCNN based grasping framework for mobile robots in unknown environments,” Expert Systems with Applications, vol. 225, Sep. 2023, Art. no. 119993. https://doi.org/10.1016/j.eswa.2023.119993
  12. N. Banerjee et al., “Lifelong mapping in the wild: Novel strategies for ensuring map stability and accuracy over time evaluated on thousands of robots,” Robotics and Autonomous Systems, vol. 164, Jun. 2023, Art. no. 104403. https://doi.org/10.1016/j.robot.2023.104403
  13. S.-H. Chan, P.-T. Wu, and L.-C. Fu, “Robust 2D indoor localization through laser slam and visual slam fusion,” in 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, Oct. 2018, pp. 1263–1268. https://doi.org/10.1109/SMC.2018.00221
  14. Y. Xu, Y. Ou, and T. Xu, “Slam of robot based on the fusion of vision and lidar,” in 2018 IEEE International Conference on Cyborg and Bionic Systems (CBS), Shenzhen, China, Oct. 2018, pp. 121–126. https://doi.org/10.1109/CBS.2018.8612212
  15. X. Xu, L. Zhang, J. Yang, C. Cao, W. Wang, Y. Ran, Z. Tan, and M. Luo, “A review of multi-sensor fusion slam systems based on 3D lidar,” Remote Sensing, vol. 14, no. 12, Jun. 2022, Art. no. 2835. https://doi.org/10.3390/rs14122835
  16. M. F. Ahmed, K. Masood, V. Fremont, and I. Fantoni, “Active slam: A review on last decade,” Sensors, vol. 23, no. 19, Sep. 2023, Art. no. 8097. https://doi.org/10.3390/s23198097
  17. H. Zhou, Z. Yao, and M. Lu, “Lidar/UWB fusion based SLAM with anti-degeneration capability,” IEEE Transactions on Vehicular Technology, vol. 70, no. 1, pp. 820–830, Dec. 2020. https://doi.org/10.1109/TVT.2020.3045767
  18. X. Dang, Z. Rong, and X. Liang, “Sensor fusion-based approach to eliminating moving objects for SLAM in dynamic environments,” Sensors, vol. 21, no. 1, Jan. 2021, Art. no. 230. https://doi.org/10.3390/s21010230
  19. I. Andersone, “Heterogeneous map merging: State of the art,” Robotics, vol. 8, no. 3, Aug. 2019, Art. no. 74. https://doi.org/10.3390/robotics8030074
  20. C. Debeunne and D. Vivet, “A review of visual-lidar fusion based simultaneous localization and mapping,” Sensors, vol. 20, no. 7, Apr. 2020, Art. no. 2068. https://doi.org/10.3390/s20072068
  21. F. Chanier, P. Checchin, C. Blanc, and L. Trassoudaine, “Map fusion based on a multi-map SLAM framework,” in 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Seoul, Korea (South), Aug. 2008, pp. 533–538. https://doi.org/10.1109/MFI.2008.4648050
  22. Y. Lu, J. Lee, S.-H. Yeh, H.-M. Cheng, B. Chen, and D. Song, “Sharing heterogeneous spatial knowledge: Map fusion between asynchronous monocular vision and lidar or other prior inputs,” in Robotics Research: The 18th International Symposium ISRR, Nov. 2020, pp. 727–741. https://doi.org/10.1007/978-3-030-28619-4_51
  23. Y. Megahed, A. Shaker, and W. Y. Yan, “Fusion of airborne lidar point clouds and aerial images for heterogeneous land-use urban mapping,” Remote Sensing, vol. 13, no. 4, Feb. 2021, Art. no. 814. https://doi.org/10.3390/rs13040814
  24. B. Zhang, J. Liu, and H. Chen, “AMCL based map fusion for multi-robot SLAM with heterogenous sensors,” in 2013 IEEE International Conference on Information and Automation (ICIA), Yinchuan, China, Aug. 2013, pp. 822–827. https://doi.org/10.1109/ICInfA.2013.6720407
  25. Z.-g. Liu, L. Zhang, G. Li, and Y. He, “Change detection in heterogeneous remote sensing images based on the fusion of pixel transformation,” in 2017 20th International Conference on Information Fusion (Fusion), Xi'an, China, Jul. 2017, pp. 1–6. https://doi.org/10.23919/ICIF.2017.8009656
DOI: https://doi.org/10.2478/acss-2024-0010 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
Language: English
Page range: 78 - 84
Submitted on: Dec 18, 2023
Accepted on: Jul 22, 2024
Published on: Aug 15, 2024
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2024 Aleksandrs Sisojevs, Aleksandrs Korsunovs, Martins Banis, Vilnis Turkovs, Reinis Cimurs, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.