Skip to main content
Log in

Autonomous MAV-based Indoor Chimney Inspection with 3D Laser Localization and Textured Surface Reconstruction

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

Inspection of industrial chimneys and smoke pipes induces high costs due to production downtimes and imposes risks to the health of human workers due to high temperatures and toxic gases. We aim at speeding up and automating this process with multicopter micro aerial vehicles. To acquire high quality sensor data, flying close to the walls of the chimney is inevitable, imposing high demands on good localization and fast and reliable control. In this paper, we present an integrated chimney inspection system based on a small lightweight flying platform, well-suited for maneuvering in narrow space. For navigation and obstacle avoidance, it is equipped with a multimodal sensor setup including a lightweight rotating 3D laser scanner, stereo cameras for visual odometry and high-resolution surface inspection. We tested our system in a decommissioned industrial chimney at the Zollverein UNESCO world heritage site and present results from autonomous flights and reconstructions of the chimney surface.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Agarwal, S., Mierle, K., et al.: Ceres solver. [online] https://ceres-solver.org https://ceres-solver.org (2016)

  2. Beul, M., Krombach, N., Zhong, Y., Droeschel, D., Nieuwenhuisen, M., Behnke, S.: A high-performance MAV for autonomous navigation in complex 3D environments. In: Int. Conf. on Unmanned Aircraft Systems (ICUAS) (2015)

  3. Blanco, J.-L.: A tutorial on SE(3) transformation parameterizations and on-manifold optimization. Technical report. University of Malaga (2010)

  4. Burri, M., Nikolic, J., Hürzeler, C., Caprari, G., Siegwart, R.: Aerial service robots for visual inspection of thermal power plant boiler systems. In: Proc. of Int. Conf. on Applied Robotics for the Power Industry (CARPI) (2012)

  5. Chan, B., Guan, H., Jo, J., Blumenstein, M.: Towards UAV-based bridge inspection systems: A review and an application perspective. Structural Monitoring and Maintenance 2(3), 283–300 (2015)

    Article  Google Scholar 

  6. Droeschel, D., Stückler, J., Behnke, S.: Local multi-resolution representation for 6D motion estimation and mapping with a continuously rotating 3D laser scanner. In: Int. Conf. on Robotics and Automation (ICRA) (2014)

  7. Engel, J., Usenko, V., Cremers, D.: A photometrically calibrated benchmark for monocular visual odometry. In arXiv:1607.02555 (2016)

  8. Fuhrmann, S., Langguth, F., Goesele, M.: MVE - a multi-view reconstruction environment. In: EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)

  9. Furgale, P., Rehder, J., Siegwart, R.: Unified temporal and spatial calibration for multi-sensor systems. In: Int. Conf. on Intelligent Robots and Systems (IROS) (2013)

  10. Geiger, A., Ziegler, J., Stiller, C.: StereoScan: Dense 3D reconstruction in real-time. In: IEEE Intelligent Vehicles Symposium (2011)

  11. Grzonka, S., Grisetti, G., Burgard, W.: A fully autonomous indoor quadrotor. IEEE Trans. Robot. 28 (1), 90–100 (2012)

    Article  Google Scholar 

  12. Holland, P., Welsch, R.: Robust regression using iteratively reweighted least-squares. Commun. Statist.-theory Methods (1977)

  13. Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. J. Opt. Soc. Amer. A 4 (4), 629–642 (1987)

    Article  Google Scholar 

  14. Houben, S., Droeschel, D., Behnke, S.: Joint 3D laser and visual fiducial marker based SLAM for a micro aerial vehicle. In: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pp. 609–614. IEEE (2016)

  15. Houben, S., Quenzel, J., Behnke, S.: Efficient multi-camera visual-inertial SLAM for micro aerial vehicles. In: Int. Conf. on Intelligent Robots and Systems (IROS) (2016)

  16. Huh, S., Shim, D., Kim, J.: Integrated navigation system using camera and gimbaled laser scanner for indoor and outdoor autonomous flight of UAVs. In: Int. Conf. on Intelligent Robots and Systems (IROS), pp. 3158–3163 (2013)

  17. Intel Corp.: Intel and Airbus demo drone inspection of passenger airliners. https://newsroom.intel.com/chip-shots/intel-airbus-demo-drone-inspection-of-passenger-airliners/ (2016)

  18. Intel Corp.: Intel RealSense camera SR300 embedded coded light 3D imaging system with full high definition color camera—product datasheet (2016)

  19. Jutzi, B., Weinmann, M., Meidow, J.: Weighted data fusion for UAV-borne 3D mapping with camera and line laser scanner. Int. J. Image Data Fusion 5(3), 226–243 (2014)

    Article  Google Scholar 

  20. Kamel, M., Burri, M., Siegwart, R.: Linear vs nonlinear MPC for trajectory tracking applied to rotary wing micro aerial vehicles. IFAC-PapersOnLine (2017)

  21. Meier, L., Tanskanen, P., Heng, L., Lee, G., Fraundorfer, F., Pollefeys, M.: PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision. Autonom. Robots 33(1–2), 21–39 (2012)

    Article  Google Scholar 

  22. Moore, R., Dantu, K., Barrows, G., Nagpal, R.: Autonomous MAV guidance with a lightweight omnidirectional vision sensor. In: Int. Conf. on Robotics and Automation (ICRA) (2014)

  23. Mur-Artal, R., Montiel, J., Tardos, J.D.: ORB-SLAM: A versatile and accurate monocular SLAM system. IEEE Trans. Robot. 31(5), 1147–1163 (2015)

    Article  Google Scholar 

  24. Nex, F., Remondino, F.: UAV for 3D mapping applications: A review. Appl. Geom. 6(1), 1–15 (2014)

    Article  Google Scholar 

  25. Nieuwenhuisen, M., Droeschel, D., Beul, M., Behnke, S.: Autonomous navigation for micro aerial vehicles in complex GNSS-denied environments. J. Intell. Robot. Syst. 84(1), 199–216 (2016)

    Article  Google Scholar 

  26. Nieuwenhuisen, M., Quenzel, J., Beul, M., Droeschel, D., Houben, S., Behnke, S.: ChimneySpector: Autonomous MAV-based indoor chimney inspection employing 3D laser localization and textured surface reconstruction. In: Int. Conf. on Unmanned Aircraft Systems (ICUAS) (2017)

  27. Nieuwenhuisen, M., Schadler, M., Behnke, S.: Predictive potential field-based collision avoidance for multicopters. In: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. (ISPRS), volume XL-1/W2, pp. 293–298 (2013)

  28. Nikolic, J., Rehder, J., Burri, M., Gohl, P., Leutenegger, S., Furgale, P.T., Siegwart, R.: A synchronized visual-inertial sensor system with FPGA pre-processing for accurate real-time SLAM. In: Int. Conf. on Robotics and Automation (ICRA) (2014)

  29. Olson, E.: AprilTag: A robust and flexible visual fiducial system. In: Int. Conf. on Robotics and Automation (ICRA) (2011)

  30. Ortiz, A., Bonnin-Pascual, F., Garcia-Fidalgo, E.: Vessel inspection: A micro-aerial vehicle-based approach. J. Intell. Robot. Syst. 76(1), 151–167 (2014)

    Article  Google Scholar 

  31. Özaslan, T., Loianno, G., Keller, J., Taylor, C.J., Kumar, V., Wozencraft, J., Hood, T.: Autonomous navigation and mapping for inspection of penstocks and tunnels with MAVs. IEEE Robot. Autom. Lett. (RAL) 2(3), 1740–1747 (2017)

    Article  Google Scholar 

  32. Park, J., Kim, Y.: 3D shape mapping of obstacle using stereo vision sensor on quadrotor UAV. In: AIAA Guidance, Navigation, and Control Conf. (2014)

  33. Quenzel, J., Rosu, R.A., Houben, S., Behnke, S.: Online depth calibration for RGB-D cameras using visual SLAM. In: Int. Conf. on Intelligent Robots and Systems (IROS) (2017)

  34. Rusu, R.B., Cousins, S.: 3D is here: Point Cloud Library (PCL). In: Int. Conf. on Robotics and Automation (ICRA) (2011)

  35. Schmid, K., Lutz, P., Tomic, T., Mair, E., Hirschmüller, H.: Autonomous vision-based micro air vehicle for indoor and outdoor navigation. J. Field Robot. 31(4), 537–570 (2014)

    Article  Google Scholar 

  36. Schönberger, J.L., Frahm, J.-M.: Structure-from-motion revisited. In: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) (2016)

  37. Schönberger, J.L., Zheng, E., Pollefeys, M., Frahm, J.-M.: Pixelwise view selection for unstructured multi-view stereo. In: European Conf. on Computer Vision (ECCV) (2016)

  38. Tomić, T., Schmid, K., Lutz, P., Domel, A., Kassecker, M., Mair, E., Grixa, I., Ruess, F., Suppa, M., Burschka, D.: Toward a fully autonomous UAV: Research platform for indoor and outdoor urban search and rescue. Robot. Autom. Mag. IEEE 19(3), 46–56 (2012)

    Article  Google Scholar 

  39. Tripathi, A., G Raja, R., Padhi, R.: Reactive collision avoidance of UAVs with stereovision camera sensors using UKF. In: International Conference on Advances in Control and Optimization of Dynamical Systems (IFAC-ACODS), pp. 1119–1125 (2014)

  40. Zhou, Q.-Y., Koltun, V.: Color map optimization for 3D reconstruction with consumer depth cameras. ACM Trans. Graph. 33(4), 155,1–155,10 (2014)

    Google Scholar 

Download references

Acknowledgments

The authors wish to thank the Autonomous Systems Lab from ETH Zürich and Ascending Technologies for their technical and organizational support, especially for providing the flying platform. We wish to thank CRN Management GmbH for building the mock-up chimney, for providing expertise for the domain of chimney inspection, and for their support during the evaluation flights. Furthermore, we wish to thank the Zollverein Foundation for the opportunity to develop and evaluate our system at the UNESCO world heritage site Zeche Zollverein.

This work was partially funded by the European Commission in the FP7 project EuRoC (grant 608849) and by the German Research Foundation (DFG) in the project Mapping on Demand (grants BE 2556/7-2 and BE 2556/8-2).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jan Quenzel.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Quenzel, J., Nieuwenhuisen, M., Droeschel, D. et al. Autonomous MAV-based Indoor Chimney Inspection with 3D Laser Localization and Textured Surface Reconstruction. J Intell Robot Syst 93, 317–335 (2019). https://doi.org/10.1007/s10846-018-0791-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-018-0791-y

Keywords

Navigation