Abstract
In this chapter we present the Autonomous Robot for Sewer Inspection (ARSI), a robotic system designed to make the work of inspection brigades safer and more efficient. ARSI uses an autonomous Micro Air Vehicle (MAV) to collect HD imagery and structural data in the sewers, while operators remain on the surface to supervise missions. Our compact quadrotor design is lightweight and robust, with a flight autonomy of 15 min and a payload capacity of 1 kg. It can be deployed without any special equipment, and operates in sewer tunnels as narrow as 80 cm. The sensor payload collects inspection data as well as inputs for the onboard software, allowing the ARSI MAV to follow pre-planned inspection paths autonomously. User-friendly interfaces are provided to plan, execute, and monitor sewer inspections. Data collected by the MAV onboard sensors is processed by our offline algorithms to generate detailed 3D models of the sewers, and perform automatic visual and structural analysis. Our data analysis software allows ARSI users to review all information and generate inspection reports for their clients. Our system was tested and validated during rigorous field tests in the city of Barcelona, Spain.
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Look@U is a GPU-based 3D dense reconstruction software system developed by Eurecat.
References
Skyfuture company. https://www.sky-futures.com/. Accessed 04 Oct 2018
Industrialskyworks company. https://industrialskyworks.com/. Accessed 04 Oct 2018
Cyberhawk company. https://www.thecyberhawk.com/. Accessed 04 Oct 2018
Airobotics company. https://www.airoboticsdrones.com/. Accessed 04 Oct 2018
Argos challenge. www.argos-challenge.com. Accessed 04 Oct 2018
European robotics challenge. http://www.euroc-project.eu/. Accessed 04 Oct 2018
Aeroarms European project. https://aeroarms-project.eu/. Accessed 04 Oct 2018
Aeroworks European project. http://www.aeroworks2020.eu/. Accessed 04 Oct 2018
Robo-spect European project. http://www.robo-spect.eu/. Accessed 04 Oct 2018
EnviroSight company. https://www.envirosight.com/. Accessed 04 Oct 2018
Ibak company. https://www.ibak.de/en/homepage/. Accessed 04 Oct 2018
Aries Industries company. https://international.ariesindustries.com/. Accessed 04 Oct 2018
SOLO from redzone company. https://www.redzone.com/technology/solo. Accessed 04 Oct 2018
KA-TE company. http://ka-te.ch/en/startseite-2/. Accessed 04 Oct 2018
Inloc robotics company. http://inlocrobotics.com/. Accessed 04 Oct 2018
Safeflight company. http://www.safeflightservices.com/. Accessed 04 Oct 2018
DJM Aerial Solutions company. https://djm-aerial.com/. Accessed 04 Oct 2018
Özaslan, T., Loianno, G., Keller, J., Taylor, C.J., Kumar, V., Wozencraft, J.M., Hood, T.: Autonomous navigation and mapping for inspection of penstocks and tunnels with mavs. IEEE Robot. Autom. Lett. 2(3), 1740–1747 (2017)
Rizzo, C., Lera, F., Villarroel, J.L.: Transversal fading analysis in straight tunnels at 2.4 GHz. In: 13th International Conference on ITS Telecommunications (ITST), pp. 313–318 (2013)
Rizzo, C., Sicignano, D., Riazuelo, L., Tardioli, D., Lera, F., Villarroel, J.L., Montano, L.: Guaranteeing communication for robotic intervention in long tunnel scenarios. In: Robot 2015: Second Iberian Robotics Conference, Advances in Robotics, vol. 1, pp. 691–703 (2016)
Rizzo, C., Cavestany, P., Chataigner, F., Soler, M., Moreno, G., Serrano, D., Lera, F., Villarroel, J.L.: Wireless propagation characterization of underground sewers towards autonomous inspections with drones. In: ROBOT 2017: Third Iberian Robotics Conference, pp. 849–860 (2018)
Labb, M., Michaud, F.: Online global loop closure detection for large-scale multi-session graph-based slam (2014)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: Orb: an efficient alternative to sift or surf (2011)
Meier, L., Honegger, D., Pollefeys, M.: PX4: a node-based multithreaded open source robotics framework for deeply embedded platforms (2015)
Gerkey, B., Konolige, K.: Planning and control in unstructured terrain (2008)
Moulon, P., Monasse, P., Marlet, R., et al.: Openmvg. An open multiple view geometry library. https://github.com/openMVG/openMVG
Fuhrmann, S., Langguth, F., Goesele, M.: A multi-view reconstruction environment. In: Eurographics Workshop on Graphics and Cultural Heritage, Darmstadt, Germany (2014)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)
LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
Shelhamer, E., Long, J., Darrell, T.: Fully convolutional networks for semantic segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(4), 640–651 (2017)
Nieuwenhuisen, M., Droeschel, D., Holz, D., Behnke, S.: Omnidirectional obstacle perception and collision avoidance for micro aerial vehicles (2013)
Acknowledgements
This work has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 601116. The authors would like to thank Mr. Raul Hernandez and the whole team at FCC (Fomento de Construcciones y Contratas) for their logistic support during the numerous field tests.
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Chataigner, F. et al. (2020). ARSI: An Aerial Robot for Sewer Inspection. In: Grau, A., Morel, Y., Puig-Pey, A., Cecchi, F. (eds) Advances in Robotics Research: From Lab to Market. Springer Tracts in Advanced Robotics, vol 132. Springer, Cham. https://doi.org/10.1007/978-3-030-22327-4_12
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