Skip to main content
SpringerLink
Log in

Rough Terrain 3D Mapping and Navigation Using a Continuously Rotating 2D Laser Scanner

  • Technical Contribution
  • Published:
KI - Künstliche Intelligenz Aims and scope Submit manuscript

Abstract

Mapping, real-time localization, and path planning are prerequisites for autonomous robot navigation. These functions also facilitate situation awareness of remote operators. In this paper, we propose methods for efficient 3D mapping and real-time 6D pose tracking of autonomous robots using a continuously rotating 2D laser scanner. We have developed our approach in the context of the DLR SpaceBot Cup robotics challenge. Multi-resolution surfel representations allow for compact maps and efficient registration of local maps. Real-time pose tracking is performed by a particle filter observing individual laser scan lines. Terrain drivability is assessed within a global environment map and used for planning feasible paths. Our approach is evaluated using challenging real environments.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Anderson S, Barfoot TD (2013) Towards relative continuous-time SLAM. In: IEEE international conference on robotics and automation (ICRA)

  2. Bosse M, Zlot R (2009) Continuous 3D scan-matching with a spinning 2D laser. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), pp 4312–4319

  3. Chen Z (2003) Bayesian filtering: from Kalman filters to particle filters, and beyond. Statistics, pp 1–69

  4. Cole D, Newman P (2006) Using laser range data for 3D SLAM in outdoor environments. In: IEEE international conference on robotics and automation (ICRA)

  5. Dellaert F, Fox D, Burgard W, Thrun S (1999) Monte Carlo localization for mobile robots. In: IEEE international conference on robotics and automation (ICRA)

  6. Elseberg J, Borrmann D, Nuechter A (2012) 6DOF semi-rigid SLAM for mobile scanning. In: IEEE/RSJ international conference on intelligent robots and systems (IROS)

  7. Ferguson D, Likhachev M (2008) Efficiently using cost maps for planning complex maneuvers. In: Proceedings of the ICRA workshop on planning with cost maps

  8. Fox D, Burgard W, Thrun S (1999) Markov localization for mobile robots in dynamic environments. J Artif Intell

  9. Gerkey BP, Konolige K (2008) Planning and control in unstructured terrain. In: Proceedings of the ICRA workshop on path planning on costmaps

  10. Hornung A, Phillips M, Jones EG, Bennewitz M, Likhachev M, Chitta S (2012) Navigation in three-dimensional cluttered environments for mobile manipulation. In: IEEE international conference on robotics and automation (ICRA)

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

    Article  Google Scholar 

  12. Huang AS, Bachrach A, Henry P, Krainin M, Maturana D, Fox D, Roy N (2011) Visual odometry and mapping for autonomous flight using an RGB-D camera. In: Proceedings of the international symposium on robotics research (ISRR)

  13. Kewlani G, Ishigami G, Iagnemma K (2009) Stochastic mobility-based path planning in uncertain environments. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 1183–1189

  14. Khoshelham K (2010) Automated localization of a laser scanner in indoor environments using planar objects. In: International conference on indoor positioning and navigation

  15. Klaess J, Stueckler J, Behnke S (2012) Efficient mobile robot navigation using 3D surfel grid maps. In: Proceedings of the German conference on robotics (ROBOTIK)

  16. Kuemmerle R, Grisetti G, Strasdat H, Konolige K, Burgard W (2011) G2o: a general framework for graph optimization. In: IEEE international conference on robotics and automation (ICRA), pp 3607–3613

  17. Kuemmerle R, Triebel R, Pfaff P, Burgard W (2007) Monte Carlo localization in outdoor terrains using multi-level surface maps. In: Proceedings of the international conference on field and service robotics (FSR)

  18. Kwak J, Pivtoraiko M, Simmons R (2008) Combining cost and reliability for rough terrain navigation. In: 9th international symposium on artificial intelligence, robotics and automation in space (iSAIRAS)

  19. Lee J, Pippin C, Balch T (2008) Cost based planning with rrt in outdoor environments. In: IEEE/RSJ international conference on intelligent robots and systems (IROS)

  20. Lin KH, Chang CH, Dopfer A, Wang CC (2012) Mapping and localization in 3D environments using a 2D laser scanner and a stereo camera. J Inf Sci Eng 28:131–144

    MathSciNet  Google Scholar 

  21. Maddern W, Harrison A, Newman P (2012) Lost in translation (and rotation): fast extrinsic calibration for 2D and 3D LIDARs. In: IEEE international conference on robotics and automation (ICRA)

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

    Article  Google Scholar 

  23. Nuechter A, Lingemann K, Hertzberg J, Surmann H (2005) 6D SLAM with approximate data association. In: International conference on advanced robotics, pp 242–249

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

    Article  Google Scholar 

  25. Schwarz M, Behnke S (2014) Local navigation in rough terrain using omnidirectional height. In: Proceedings of the German conference on robotics (ROBOTIK)

  26. Stoyanov T, Lilienthal A (2009) Maximum likelihood point cloud acquisition from a mobile platform. In: International conference on advanced robotics (ICAR), pp 1–6

  27. Stoyanov T, Magnusson M, Andreasson H, Lilienthal AJ (2010) Path planning in 3D environments using the normal distributions transform. In: IEEE/RSJ international conference on intelligent robots and systems (IROS)

  28. Stückler J, Behnke S (2014) Multi-resolution surfel maps for efficient dense 3D modeling and tracking. J Vis Commun Image Represen 25(1):137–147

    Article  Google Scholar 

  29. Tong C, Gingras D, Larose K, Barfoot T, Dupuis E (2013) The canadian planetary emulation terrain 3D mapping dataset. Int J Robot Res (IJRR)

  30. Triebel R, Pfaff P, Burgard W (2006) Multi-level surface maps for outdoor terrain mapping and loop closing. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems

Download references

Author information

Authors and Affiliations

  1. Autonomous Intelligent Systems, Computer Science Institute VI, University of Bonn, Bonn, Germany

    Mark Schadler, Jörg Stückler & Sven Behnke

Authors
  1. Mark Schadler
    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 Mark Schadler.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schadler, M., Stückler, J. & Behnke, S. Rough Terrain 3D Mapping and Navigation Using a Continuously Rotating 2D Laser Scanner. Künstl Intell 28, 93–99 (2014). https://doi.org/10.1007/s13218-014-0301-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13218-014-0301-8

Keywords

Search

Navigation