The article addresses the issues of digital mapping of territories using modern equipment and innovative methods for performing topographic and geodetic work. Objective: To study modern territorial mapping methods and justify mapping approaches using SLAM technology. Methods and Results: The study employed a territorial mapping method using handheld laser scanners with SLAM technology. Terrain reconnaissance was conducted, control geodetic points were established, and fieldwork was performed using a Stonex X120GO scanner. The acquired point clouds were compared with the tacheometric survey results. Analysis of mean square errors confirmed that the accuracy met regulatory requirements. Scientific Novelty and Practical Significance: This study enables the evaluation of SLAM technology in ground-based handheld laser scanners as an alternative to traditional topographic surveying methods. When used correctly, this type of equipment fully meets the accuracy requirements for topographic plans at a scale of 1:500 and, in some cases, even 1:200. This, in turn, creates opportunities for the broader implementation of SLAM in topographic and geodetic practices. Applying SLAM technology and modern handheld laser scanners for topographic, geodetic, and mapping tasks can significantly reduce costs, resource consumption, and labor efforts while requiring fewer personnel and pieces of equipment. The study evaluates the possibilities of using SLAM technology and its accuracy. The article proves that using SLAM technology and handheld 3D scanners is an accurate and reliable tool for performing work in modern realities.
- Alsadik, B., & Karam, S. (2021). The simultaneous localization and mapping (SLAM): An overview. Surveying and geospatial engineering journal, 1(2), 1-12. https://doi.org/10.38094/sgej1027
- Chen, M., Yang, S., Yi, X., & Wu, D. (2017, July). Real-time 3D mapping using a 2D laser scanner and IMU-aided visual SLAM. In 2017 IEEE International Conference on Real-time Computing and Robotics (RCAR) (pp. 297-302). IEEE. https://doi.org/10.1109/RCAR.2017.8311877
- Chong, T. J., Tang, X. J., Leng, C. H., Yogeswaran, M., Ng, O. E., & Chong, Y. Z. (2015). Sensor technologies and simultaneous localization and mapping (SLAM). Procedia Computer Science, 76, 174-179. https://doi.org/10.1016/j.procs.2015.12.336
- Droeschel, D., & Behnke, S. (2018, May). Efficient continuous-time SLAM for 3D lidar-based online mapping. In 2018 IEEE International Conference on Robotics and Automation (ICRA) (pp. 5000-5007). IEEE. https://doi.org/10.1109/ICRA.2018.8461000
- Huang, L. (2021, November). Review on LiDAR-based SLAM techniques. In 2021 International conference on signal processing and machine learning (CONF-SPML) (pp. 163-168). IEEE. https://doi.org/10.1109/CONF-SPML54095.2021.00040
- Jia, S., Liu, C., Wu, H., Zeng, D., & Ai, M. (2021). A cross-correction LiDAR SLAM method for high-accuracy 2D mapping of problematic scenario. ISPRS Journal of Photogrammetry and Remote Sensing, 171, 367-384. https://doi.org/10.1016/j.isprsjprs.2020.11.004
- Kazerouni, I. A., Fitzgerald, L., Dooly, G., & Toal, D. (2022). A survey of state-of-the-art on visual SLAM. Expert Systems with Applications, 205, 117734. https://doi.org/10.1016/j.eswa.2022.117734
- Khairuddin, A. R., Talib, M. S., & Haron, H. (2015, November). Review on simultaneous localization and mapping (SLAM). In 2015 IEEE international conference on control system, computing and engineering (ICCSCE) (pp. 85-90). IEEE. https://doi.org/10.1109/ICCSCE.2015.7482163
- Kim, P., Chen, J., & Cho, Y. K. (2018). SLAM-driven robotic mapping and registration of 3D point clouds. Automation in Construction, 89, 38-48. https://doi.org/10.1016/j.autcon.2018.01.009
- Palomer, A., Ridao, P., & Ribas, D. (2019). Inspection of an underwater structure using point‐cloud SLAM with an AUV and a laser scanner. Journal of field robotics, 36(8), 1333-1344. https://doi.org/10.1002/rob.21907
- Pierzchała, M., Giguère, P., & Astrup, R. (2018). Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM. Computers and Electronics in Agriculture, 145, 217-225. https://doi.org/10.1016/j.compag.2017.12.034
- Shan, J., & Toth, C.K. (2018). Topographic Laser Ranging and Scanning: Principles and Processing (2nd ed.). Taylor & Francis Group. https://doi.org/10.1016/j.compag.2017.12.034
- Taheri, H., & Xia, Z. C. (2021). SLAM; definition and evolution. Engineering Applications of Artificial Intelligence, 97, 104032. https://doi.org/10.1016/j.engappai.2020.104032
- Yue, X., Zhang, Y., Chen, J., Chen, J., Zhou, X., & He, M. (2024). LiDAR-based SLAM for robotic mapping: state of the art and new frontiers. Industrial Robot: the international journal of robotics research and application, 51(2), 196-205. https://doi.org/10.1108/IR-09-2023-0225
- Zhang, S., Zheng, L., & Tao, W. (2021). Survey and evaluation of RGB-D SLAM. IEEE Access, 9, 21367-21387. https://doi.org/10.1109/ACCESS.2021.3053188
- Zhang, Y., Shi, P., & Li, J. (2024). 3d lidar slam: A survey. The Photogrammetric Record, 39(186), 457-517. https://doi.org/10.1111/phor.12497