Skip to main content
SpringerLink
Log in

Local Multi-resolution Surfel Grids for MAV Motion Estimation and 3D Mapping

  • Conference paper
  • First Online:
Intelligent Autonomous Systems 13

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 302))

Abstract

For autonomous navigation in restricted environments, micro aerial vehicles (MAV) need to create 3D maps of their surroundings and must track their motion within these maps. In this paper, we propose an approach to simultaneous localization and mapping that is based on the measurements of a lightweight 3D laser-range finder. We aggregate laser-range measurements by registering sparse 3D scans with a local multiresolution surfel map that has high resolution in the vicinity of the MAV and coarser resolutions with increasing distance, which corresponds well to measurement density and accuracy of our sensor. Modeling measurement distributions within voxels by surface elements allows for efficient and accurate registration of 3D scans with the local map. The incrementally built local dense 3D maps of nearby key poses are registered globally by graph optimization. This yields a globally consistent dense 3D map of the environment. Continuous registration of local maps with the global map allows for tracking the 6D MAV pose in real time. In experiments, we demonstrate accuracy and efficiency of our approach.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Anderson, S., Barfoot, T.D.: Towards relative continuous-time SLAM. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA) (2013)

    Google Scholar 

  2. Bachrach, A., He, R., Roy, N.: Autonomous flight in unstructured and unknown indoor environments. In: European Micro Aerial Vehicle Conf (EMAV) (2009)

    Google Scholar 

  3. Bishop, C.M.: Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York Inc, Secaucus, NJ, USA (2006)

    Google Scholar 

  4. Bosse, M., Zlot, R.: Continuous 3D scan-matching with a spinning 2D laser. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA) (2009)

    Google Scholar 

  5. Cover, H., Choudhury, S., Scherer, S., Singh, S.: Sparse tangential network (SPARTAN): Motion planning for micro aerial vehicles. In: Robotics and Automation (ICRA), IEEE International Conference on (2013)

    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: Robotics and Automation (ICRA), IEEE International Conference on (2014)

    Google Scholar 

  7. Elseberg, J., Borrmann, D., Nuechter, A.: 6DOF semi-rigid SLAM for mobile scanning. In: Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on (2012)

    Google Scholar 

  8. Grzonka, S., Grisetti, G., Burgard, W.: Towards a navigation system for autonomous indoor flying. In: Robotics and Automation (ICRA), IEEE International Conference on (2009)

    Google Scholar 

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

    Google Scholar 

  10. Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Autonomous Robots 34, 189–206 (2013)

    Google Scholar 

  11. Huh, S., Shim, D., Kim, J.: Integrated navigation system using camera and gimbaled laser scanner for indoor and outdoor autonomous flight of UAVs. In: Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on (2013)

    Google Scholar 

  12. Kuemmerle, R., Grisetti, G., Strasdat, H., Konolige, K., Burgard, W.: G2o: A general framework for graph optimization. In: Robotics and Automation (ICRA), IEEE International Conference on (2011)

    Google Scholar 

  13. Maddern, W., Harrison, A., Newman, P.: Lost in translation (and rotation): Fast extrinsic calibration for 2D and 3D LIDARs. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA) (May 2012)

    Google Scholar 

  14. Magnusson, M., Duckett, T., Lilienthal, A.J.: Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics 24(10), 803–827 (2007)

    Google Scholar 

  15. Myronenko, A., Song, X.: Point set registration: Coherent point drift. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(12), 2262–2275 (2010)

    Google Scholar 

  16. Nieuwenhuisen, M., Droeschel, D., Schneider, J., Holz, D., Läbe, T., Behnke, S.: Multimodal obstacle detection and collision avoidance for micro aerial vehicles. In: Proceedings of 6th European Conference on Mobile Robots (ECMR) (2013)

    Google Scholar 

  17. Nuechter, A., Lingemann, K., Hertzberg, J., Surmann, H.: 6D SLAM with approximate data association. In: Int. Conf. on Advanced Robotics (2005)

    Google Scholar 

  18. Ryde, J., Hu, H.: 3D mapping with multi-resolution occupied voxel lists. Autonomous Robots 28, 169–185 (2010)

    Google Scholar 

  19. Schadler, M., Stückler, J., Behnke, S.: Multi-resolution surfel mapping and real-time pose tracking using a continuously rotating 2D laser scanner. In: Proc. of 11th IEEE Int. Symposium on Safety, Security, and Rescue Robotics (SSRR) (2013)

    Google Scholar 

  20. Scherer, S., Rehder, J., Achar, S., Cover, H., Chambers, A.D., Nuske, S.T., Singh, S.: River mapping from a flying robot: State estimation, river detection, and obstacle mapping. Autonomous Robots 32(5), 1–26 (May 2012)

    Google Scholar 

  21. Schneider, J., Läbe, T., Förstner, W.: Incremental real-time bundle adjustment for multi-camera systems with points at infinity. In: ISPRS Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. XL-1/W2 (2013)

    Google Scholar 

  22. Segal, A., Hähnel, D., Thrun, S.: Generalized-ICP. In: Proc. of Robotics: Science and Systems (RSS) (2009)

    Google Scholar 

  23. Shen, S., Michael, N., Kumar, V.: Autonomous multi-floor indoor navigation with a computationally constrained micro aerial vehicle. In: Robotics and Automation (ICRA), IEEE International Conference on (2011)

    Google Scholar 

  24. Stoyanov, T., Lilienthal, A.: Maximum likelihood point cloud acquisition from a mobile platform. In: Proc. of the Int. Conf. on Advanced Robotics (ICAR) (2009)

    Google Scholar 

  25. Stückler, J., Behnke, S.: Multi-resolution surfel maps for efficient dense 3D modeling and tracking. Journal of Visual Communication and Image Representation 25(1), 137–147 (2014)

    Google Scholar 

  26. Takahashi, M., Schulein, G., Whalley, M.: Flight control law design and development for an autonomous rotorcraft. In: Proceedings of the 64th Annual Forum of the American Helicopter Society (2008)

    Google Scholar 

  27. Thrun, S., Diel, M., Hähnel, D.: Scan alignment and 3-d surface modeling with a helicopter platform. In: FSR. Springer Tracts in Advanced Robotics, vol. 24, pp. 287–297. Springer (2003)

    Google Scholar 

  28. 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. Robotics Automation Magazine, IEEE 19(3), 46–56 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Institute VI, University of Bonn, 53113, Bonn, Germany

    David Droeschel, Jörg Stückler & Sven Behnke

Authors
  1. David Droeschel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jörg Stückler
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sven Behnke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David Droeschel .

Editor information

Editors and Affiliations

  1. Information Engineering, University of Padua, Padua, Italy

    Emanuele Menegatti

  2. Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nathan Michael

  3. Fachbereich Informatik, Technische Universität Kaiserslautern Arbeitsgruppe Robotersysteme, Kaiserslautern, Germany

    Karsten Berns

  4. Integrated Information Technology, Aoyama Gakuin University, Tokyo, Japan

    Hiroaki Yamaguchi

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Droeschel, D., Stückler, J., Behnke, S. (2016). Local Multi-resolution Surfel Grids for MAV Motion Estimation and 3D Mapping. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08338-4_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08337-7

  • Online ISBN: 978-3-319-08338-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation