Skip to main content

Traversability Classification Using Super-voxel Method in Unstructured Terrain

  • Conference paper
Robot Intelligence Technology and Applications 3

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 345))

  • 3919 Accesses

Abstract

Estimating the traversability of terrain in an unstructured outdoor environment is one of the challenging issues in autonomous vehicles. When dealing with a large 3D point cloud, the computational cost of processing all of the individual points is very high. Thus voxelization methods are used extensively. In this paper, we propose a more fine-grained voxelization algorithm in the context of unstructured terrain classification. While the current shape of a voxel is a fixed-length cubic, we construct a flexible shape voxel which has spatial and geometrical properties. Furthermore, we propose a new shape histogram feature that represents the statistical characteristics of 3D points. The proposed method was tested using data obtained from unstructured outdoor environments for performance evaluation.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Heckman, N., et al.: Potential negative obstacle detection by occlusion labeling. IEEE/RSJ. Int. Conf. Intell. Rob. & Syst (2007)

    Google Scholar 

  2. Stoyanov, T., et al.: Path planning in 3D environments using the normal distributions transform. IEEE/RSJ Int. Conf. Intell. Rob. & Syst (2010)

    Google Scholar 

  3. Bogil, S., Myungjin, C.: Traversable ground detection based on geometric-featured voxel map. In: Bogil, S., Myungjin, C. (eds.) IEEE. Korea-Japan Joint Workshop on Frontiers of Computer Vision, pp. 31–35 (2013)

    Google Scholar 

  4. Papon, J., et al.: Voxel cloud connectivity segmentation-supervoxels for point clouds. In: IEEE Conf. Computer Vision and Pattern Recognition, pp. 2027–2034 (2013)

    Google Scholar 

  5. Lalonde, J.F., Vandapel, N., Huber, D.F., Hebert, M.: Natural terrain classification using three-dimensional ladar data for ground robot mobility. Journal of Field Robotics 23(10), 839–861 (2006)

    Article  Google Scholar 

  6. Rabbani, T., van den Heuvel, F., Vosselmann, G.: Segmentation of point clouds using smoothness constraint. In: Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 248–253 (2006)

    Google Scholar 

  7. Rusu, R., et al.: Learning informative point classes for the acquisition of object model maps. In: IEEE. Int. Conf. Control, Automation, Robotics and Vision, pp. 643–650 (2008)

    Google Scholar 

  8. Rusu, R., Blodow, N., Beetz, M.: Fast point feature histograms (FPFH) for 3D registration. In: IEEE Int. Conf. on Rob. & Autom (2009)

    Google Scholar 

  9. Yungeun, C., Seunguk, A., MyungJin, C.: Online urban object recognition in point clouds using consecutive point information for urban robotic missions. Robotics and Autonomous Systems (2014)

    Google Scholar 

  10. Dongshin, K., et al.: Traversability classification using unsupervised on-line visual learning for outdoor robot navigation. In: IEEE Int. Conf. on Rob. & Autom. (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Soohwan Song .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Song, S., Jo, S. (2015). Traversability Classification Using Super-voxel Method in Unstructured Terrain. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-16841-8_53

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16840-1

  • Online ISBN: 978-3-319-16841-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics