Optimasi Pengukuran Dinamis dari Visualisasi Model Ruangan 3D Menggunakan Sensor LiDAR dan Framework RoomPlan
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Sep 20, 2024
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Utilizing limited space to be more functional and aesthetic, such as adding furniture or using it as gardening space, can be achieved through effective room mapping. However, manual mapping methods have limitations such as inaccurate measurements, time efficiency, and also lack of room visualization. In this modern era, robotics technology has been widely applied in everyday life, one of which is the use of LiDAR sensors for room mapping. This paper discusses a room mapping system using a mobile application that utilizes LiDAR sensors. The mapping process is carried out by scanning the area to be mapped and rotating the area 360 degrees. The result of this mapping is a scanned 3D model of the room, which allows measurements from every side of the room. Research shows that the mapping results from the software created are similar in shape to actual field conditions. In addition, the measurement accuracy only has a small difference of 0.2%. It is hoped that this research can make it easier for humans to map rooms and make better use of limited space.
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LiDAR ; Room Mapping ; 3D
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Mulyana, D. I., & Pratiwi, T. A. (2024). Optimasi Pengukuran Dinamis dari Visualisasi Model Ruangan 3D Menggunakan Sensor LiDAR dan Framework RoomPlan. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(3), 2623-2633. https://doi.org/10.35870/jimik.v5i3.950
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References
Aziz, F. N., & Zakarijah, M. (2022). Analisis Kinerja Sensor TF-Mini LiDAR untuk Pengukuran Jarak. Jurnal Nasional Teknik Elektro dan Teknologi Informasi, 11(3), 192-198. DOI: https://doi.org/10.22146/jnteti.v11i3.3814.
Boniardi, F., Caselitz, T., Kümmerle, R., & Burgard, W. (2017, September). Robust LiDAR-based localization in architectural floor plans. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3318-3324). IEEE. DOI: 10.1109/IROS.2017.8206168.
Bybee, T. C., & Budge, S. E. (2019). Method for 3-D scene reconstruction using fused LiDAR and imagery from a texel camera. IEEE Transactions on Geoscience and Remote Sensing, 57(11), 8879-8889. DOI: 10.1109/TGRS.2019.2923551.
Chan, T. H., Hesse, H., & Ho, S. G. (2021, April). Lidar-based 3d slam for indoor mapping. In 2021 7th international conference on control, automation and robotics (ICCAR) (pp. 285-289). IEEE. DOI: 10.1109/ICCAR52225.2021.9463503.
Cui, Y., Li, Q., Yang, B., Xiao, W., Chen, C., & Dong, Z. (2019). Automatic 3-D reconstruction of indoor environment with mobile laser scanning point clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(8), 3117-3130. DOI: 10.1109/JSTARS.2019.2918937.
Dong, P., & Chen, Q. (2017). LiDAR remote sensing and applications. CRC Press.
Erturan, A. M., Durdu, A., & Erturan, E. M. (2019). The Use of LIDAR Technology in Architectural Offices. European Journal of Engineering Science and Technology, 2(2), 40-48.
Fang, H., Lafarge, F., Pan, C., & Huang, H. (2021). Floorplan generation from 3D point clouds: A space partitioning approach. ISPRS Journal of Photogrammetry and Remote Sensing, 175, 44-55. DOI: https://doi.org/10.1016/j.isprsjprs.2021.02.012.
He, Z., Hou, J., & Schwertfeger, S. (2019, December). Furniture free mapping using 3d lidars. In 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 583-589). IEEE.
Li, Z., Chen, J., & Baltsavias, E. (Eds.). (2008). Advances in photogrammetry, remote sensing and spatial information sciences: 2008 ISPRS congress book (Vol. 7). CRC Press.
Mana, S. M., Gabra, K. G., Kouhini, S. M., Hinrichs, M., Schulz, D., Hellwig, P., ... & Jungnickel, V. (2022). LiDAR-assisted channel modelling for LiFi in realistic indoor scenarios. IEEE Access, 10, 59383-59399. DOI: 10.1109/ACCESS.2022.3176353.
Maulana, I., Rusdinar, A., & Priramadhi, R. A. (2018). Lidar application for mapping and robot navigation on closed environment. JMECS (Journal of Measurements, Electronics, Communications, and Systems), 4(1), 20-26. DOI: https://doi.org/10.25124/jmecs.v4i1.1696.
Parent, J. R., Witharana, C., & Bradley, M. (2021). Mapping building interiors with LiDAR: Classifying the point cloud with ArcGIS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 133-137.
Poux, F., & Billen, R. (2019). A smart point cloud infrastructure for intelligent environments. In Laser Scanning (pp. 127-149). CRC Press.
Prayoga, S., Budianto, A., & Atmaja, A. B. K. (2017). Sistem Pemetaan Ruangan 2D Menggunakan Lidar. Jurnal Integrasi, 9(1), 73-79. DOI: https://doi.org/10.30871/ji.v9i1.273.
Song, S., & Myung, H. (2021, July). Floorplan-based localization and map update using lidar sensor. In 2021 18th International Conference on Ubiquitous Robots (UR) (pp. 30-34). IEEE. DOI: 10.1109/UR52253.2021.9494685.
Teo, T. A., & Yang, C. C. (2023). Evaluating the accuracy and quality of an iPad Pro's built-in lidar for 3D indoor mapping. Developments in the Built Environment, 14, 100169.
Turner, E., Cheng, P., & Zakhor, A. (2014). Fast, automated, scalable generation of textured 3D models of indoor environments. IEEE Journal of Selected Topics in Signal Processing, 9(3), 409-421. DOI: 10.1109/JSTSP.2014.2381153.
Ungureanu, V. I., Trutiu, B. A., Silea, I., Negîrla, P., Zimbru, C., & Miclea, R. C. (2019, May). Automatic Mapping of a Room Using LIDAR-Based Measuring Sensor. In 2019 22nd International Conference on Control Systems and Computer Science (CSCS) (pp. 689-695). IEEE. DOI: 10.1109/CSCS.2019.00123.
Wang, C., Yang, X., Xi, X., Nie, S., & Dong, P. (2024). Introduction to LiDAR remote sensing. CRC Press.
Wang, Q., Tan, Y., & Mei, Z. (2020). Computational methods of acquisition and processing of 3D point cloud data for construction applications. Archives of computational methods in engineering, 27(2), 479-499.
Wen, C., Tan, J., Li, F., Wu, C., Lin, Y., Wang, Z., & Wang, C. (2021). Cooperative indoor 3D mapping and modeling using LiDAR data. Information Sciences, 574, 192-209. DOI: https://doi.org/10.1016/j.ins.2021.06.006.
Yan, J., Zhang, K., Zhang, C., Chen, S. C., & Narasimhan, G. (2014). Automatic construction of 3-D building model from airborne LiDAR data through 2-D snake algorithm. IEEE Transactions on Geoscience and Remote Sensing, 53(1), 3-14. DOI: 10.1109/TGRS.2014.2312393.
Yao, W., & Wei, Y. (2013). Detection of 3-D individual trees in urban areas by combining airborne LiDAR data and imagery. IEEE Geoscience and Remote Sensing Letters, 10(6), 1355-1359. DOI: 10.1109/LGRS.2013.2241390.
Zimmerman, N., Guadagnino, T., Chen, X., Behley, J., & Stachniss, C. (2022). Long-term localization using semantic cues in floor plan maps. IEEE Robotics and Automation Letters, 8(1), 176-183. DOI: 10.1109/LRA.2022.3223556.
Boniardi, F., Caselitz, T., Kümmerle, R., & Burgard, W. (2017, September). Robust LiDAR-based localization in architectural floor plans. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3318-3324). IEEE. DOI: 10.1109/IROS.2017.8206168.
Bybee, T. C., & Budge, S. E. (2019). Method for 3-D scene reconstruction using fused LiDAR and imagery from a texel camera. IEEE Transactions on Geoscience and Remote Sensing, 57(11), 8879-8889. DOI: 10.1109/TGRS.2019.2923551.
Chan, T. H., Hesse, H., & Ho, S. G. (2021, April). Lidar-based 3d slam for indoor mapping. In 2021 7th international conference on control, automation and robotics (ICCAR) (pp. 285-289). IEEE. DOI: 10.1109/ICCAR52225.2021.9463503.
Cui, Y., Li, Q., Yang, B., Xiao, W., Chen, C., & Dong, Z. (2019). Automatic 3-D reconstruction of indoor environment with mobile laser scanning point clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(8), 3117-3130. DOI: 10.1109/JSTARS.2019.2918937.
Dong, P., & Chen, Q. (2017). LiDAR remote sensing and applications. CRC Press.
Erturan, A. M., Durdu, A., & Erturan, E. M. (2019). The Use of LIDAR Technology in Architectural Offices. European Journal of Engineering Science and Technology, 2(2), 40-48.
Fang, H., Lafarge, F., Pan, C., & Huang, H. (2021). Floorplan generation from 3D point clouds: A space partitioning approach. ISPRS Journal of Photogrammetry and Remote Sensing, 175, 44-55. DOI: https://doi.org/10.1016/j.isprsjprs.2021.02.012.
He, Z., Hou, J., & Schwertfeger, S. (2019, December). Furniture free mapping using 3d lidars. In 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 583-589). IEEE.
Li, Z., Chen, J., & Baltsavias, E. (Eds.). (2008). Advances in photogrammetry, remote sensing and spatial information sciences: 2008 ISPRS congress book (Vol. 7). CRC Press.
Mana, S. M., Gabra, K. G., Kouhini, S. M., Hinrichs, M., Schulz, D., Hellwig, P., ... & Jungnickel, V. (2022). LiDAR-assisted channel modelling for LiFi in realistic indoor scenarios. IEEE Access, 10, 59383-59399. DOI: 10.1109/ACCESS.2022.3176353.
Maulana, I., Rusdinar, A., & Priramadhi, R. A. (2018). Lidar application for mapping and robot navigation on closed environment. JMECS (Journal of Measurements, Electronics, Communications, and Systems), 4(1), 20-26. DOI: https://doi.org/10.25124/jmecs.v4i1.1696.
Parent, J. R., Witharana, C., & Bradley, M. (2021). Mapping building interiors with LiDAR: Classifying the point cloud with ArcGIS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 133-137.
Poux, F., & Billen, R. (2019). A smart point cloud infrastructure for intelligent environments. In Laser Scanning (pp. 127-149). CRC Press.
Prayoga, S., Budianto, A., & Atmaja, A. B. K. (2017). Sistem Pemetaan Ruangan 2D Menggunakan Lidar. Jurnal Integrasi, 9(1), 73-79. DOI: https://doi.org/10.30871/ji.v9i1.273.
Song, S., & Myung, H. (2021, July). Floorplan-based localization and map update using lidar sensor. In 2021 18th International Conference on Ubiquitous Robots (UR) (pp. 30-34). IEEE. DOI: 10.1109/UR52253.2021.9494685.
Teo, T. A., & Yang, C. C. (2023). Evaluating the accuracy and quality of an iPad Pro's built-in lidar for 3D indoor mapping. Developments in the Built Environment, 14, 100169.
Turner, E., Cheng, P., & Zakhor, A. (2014). Fast, automated, scalable generation of textured 3D models of indoor environments. IEEE Journal of Selected Topics in Signal Processing, 9(3), 409-421. DOI: 10.1109/JSTSP.2014.2381153.
Ungureanu, V. I., Trutiu, B. A., Silea, I., Negîrla, P., Zimbru, C., & Miclea, R. C. (2019, May). Automatic Mapping of a Room Using LIDAR-Based Measuring Sensor. In 2019 22nd International Conference on Control Systems and Computer Science (CSCS) (pp. 689-695). IEEE. DOI: 10.1109/CSCS.2019.00123.
Wang, C., Yang, X., Xi, X., Nie, S., & Dong, P. (2024). Introduction to LiDAR remote sensing. CRC Press.
Wang, Q., Tan, Y., & Mei, Z. (2020). Computational methods of acquisition and processing of 3D point cloud data for construction applications. Archives of computational methods in engineering, 27(2), 479-499.
Wen, C., Tan, J., Li, F., Wu, C., Lin, Y., Wang, Z., & Wang, C. (2021). Cooperative indoor 3D mapping and modeling using LiDAR data. Information Sciences, 574, 192-209. DOI: https://doi.org/10.1016/j.ins.2021.06.006.
Yan, J., Zhang, K., Zhang, C., Chen, S. C., & Narasimhan, G. (2014). Automatic construction of 3-D building model from airborne LiDAR data through 2-D snake algorithm. IEEE Transactions on Geoscience and Remote Sensing, 53(1), 3-14. DOI: 10.1109/TGRS.2014.2312393.
Yao, W., & Wei, Y. (2013). Detection of 3-D individual trees in urban areas by combining airborne LiDAR data and imagery. IEEE Geoscience and Remote Sensing Letters, 10(6), 1355-1359. DOI: 10.1109/LGRS.2013.2241390.
Zimmerman, N., Guadagnino, T., Chen, X., Behley, J., & Stachniss, C. (2022). Long-term localization using semantic cues in floor plan maps. IEEE Robotics and Automation Letters, 8(1), 176-183. DOI: 10.1109/LRA.2022.3223556.