Sistema BIM2ROS para la integración de robots aéreos en el sector de la construcción

  1. Santiago Martínez Navarro
  2. Cobano Suárez, José Antonio 1
  3. Merino, Luis 1
  4. Caballero, Fernando 1
  1. 1 Universidad Pablo de Olavide
Journal:
Jornadas de Automática

ISSN: 3045-4093

Year of publication: 2024

Issue: 45

Type: Article

DOI: 10.17979/JA-CEA.2024.45.10974 DIALNET GOOGLE SCHOLAR

Abstract

The construction sector is one of the least digitized, and robotics, drones, and Building Information Modeling (BIM) can play a fundamental role in this digitalization. Most robotic solutions rely on teleoperation by workers, but thanks to all the information available in BIM, these processes can be automated to be carried out by mobile robots or drones. This paper addresses the integration of robots in the construction field, taking advantage of all the information that BIM can provide, both geometric andsemantic. We present a system called BIM2ROS. The integration is carried out by generating all the necessary information for the robot to work with ROS (Robot Operating System) from the BIM. Once the robot’s world is generated, the semantic information is included in the path planning to navigate into the building, and an identification of the building components constructed from a 3D lidar sensor on board the drone and the BIM information is also performed. Experimental results are presented in a building to demonstrate as the system works, planning, and element identification.

Bibliographic References

  • Bartolomei, L., Teixeira, L., Chli, M., 2020. Perception-aware path planning for uavs using semantic segmentation. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 5808–5815. DOI: 10.1109/IROS45743.2020.9341347 DOI: https://doi.org/10.1109/IROS45743.2020.9341347
  • Bastianelli, E., Bloisi, D., Capobianco, R., Cossu, F., Gemignani, G., Iocchi, L., Nardi, D., 11 2013. On-line semantic mapping. DOI: 10.1109/ICAR.2013.6766501 DOI: https://doi.org/10.1109/ICAR.2013.6766501
  • Chau, K., Anson, M., Zhang, J., 08 2004. Four-dimensional visualization of construction scheduling and site utilization. Journal of Construction Engineering and Management 130. DOI: 10.1061/(ASCE)0733-9364(2004)130:4(598) DOI: https://doi.org/10.1061/(ASCE)0733-9364(2004)130:4(598)
  • Cobano, J. A., Rey, R., Merino, L., Caballero, F., 2022. Fast cost-aware lazytheta over euclidean distance functions for 3d planning of aerial robots in building-like environments. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 13486–13493. DOI: 10.1109/IROS47612.2022.9982180 DOI: https://doi.org/10.1109/IROS47612.2022.9982180
  • Correa, F., 07 2016. Robot-oriented design for production in the context of building information modeling. DOI: 10.22260/ISARC2016/0103 DOI: https://doi.org/10.22260/ISARC2016/0103
  • Deeken, H., Puetz, S., Wiemann, T., Lingemann, K., Hertzberg, J., 2014. Integrating semantic information in navigational planning. In: ISR/Robotik 2014; 41st International Symposium on Robotics. pp. 1–8.
  • Follini, C., Magnago, V., Freitag, K., Terzer, M., Marcher, C., Riedl, M., Giusti, A., Matt, D., 12 2020. Bim-integrated collaborative robotics for application in building construction and maintenance. Robotics 10, 2. DOI: 10.3390/robotics10010002 DOI: https://doi.org/10.3390/robotics10010002
  • Hamieh, A., Ben Makhlouf, A., Louhichi, B., Deneux, D., 2020. A bim-based method to plan indoor paths. Automation in Construction 113, 103120. DOI: 10.1016/j.autcon.2020.103120 DOI: https://doi.org/10.1016/j.autcon.2020.103120
  • Jin, R., Zhong, B., Ma, L., Hashemi, A., Ding, L., 2019. Integrating bim with building performance analysis in project life-cycle. Automation in Construction 106, 102861. DOI: 10.1016/j.autcon.2019.102861 DOI: https://doi.org/10.1016/j.autcon.2019.102861
  • Kim, K., Peavy, M., 2022. Bim-based semantic building world modeling for robot task planning and execution in built environments. Automation in Construction 138, 104247. DOI: 10.1016/j.autcon.2022.104247 DOI: https://doi.org/10.1016/j.autcon.2022.104247
  • Naik, L., Blumenthal, S., Huebel, N., Bruyninckx, H., Prassler, E., 2019. Semantic mapping extension for openstreetmap applied to indoor robot navigation. In: 2019 International Conference on Robotics and Automation (ICRA). pp. 3839–3845. DOI: 10.1109/ICRA.2019.8793641 DOI: https://doi.org/10.1109/ICRA.2019.8793641
  • Nash, S. K., Tovey, C., 2010. Lazy theta*: Any-angle path planning and path length analysis in 3d. In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI). p. 147–154. DOI: https://doi.org/10.1609/aaai.v24i1.7566
  • Pan, Z., Yu, Y., Xiao, F., Zhang, J., 2023. Recovering building information model from 2d drawings for mechanical, electrical and plumbing systems of ageing buildings. Automation in Construction 152, 104914. DOI: 10.1016/j.autcon.2023.104914 DOI: https://doi.org/10.1016/j.autcon.2023.104914
  • Pauwels, P., de Koning, R., Hendrikx, B., Torta, E., 2023. Live semantic data from building digital twins for robot navigation: Overview of data transfer methods. Advanced Engineering Informatics 56, 101959. DOI: 10.1016/j.aei.2023.101959 DOI: https://doi.org/10.1016/j.aei.2023.101959
  • Perez-Grau, F. J., Caballero, F., Merino, L., Viguria, A., 2017. Multi-modalmapping and localization of unmanned aerial robots based on ultra wideband and rgb-d sensing. In: 2017 IEEE/RSJ International Conferenceon Intelligent Robots and Systems (IROS). pp. 3495–3502. DOI: 10.1109/IROS.2017.8206191 DOI: https://doi.org/10.1109/IROS.2017.8206191
  • Zhao, Y., Liu, P., Xue, W., Miao, R., Gong, Z., Ying, R., 2019. Semantic probabilistic traversable map generation for robot path planning. In: 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO). pp. 2576–2582. DOI: 10.1109/ROBIO49542.2019.8961533 DOI: https://doi.org/10.1109/ROBIO49542.2019.8961533
Data source: Dialnet