Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Airborne Monocular Vision Guidance Method for Autonomous Landing

  • Conference paper
  • First Online:
Proceedings of the 6th China Aeronautical Science and Technology Conference (CASTC 2023)

Abstract

Vision guidance has shown increasingly promising capacity in autonomous landing, since it has the merits of low-cost and electromagnetic resistance. In this work, we propose an airborne monocular vision guidance method using region and structured line features. In the approach phase, a region-based pose tracker is adopted to track the pose within the consecutive frames using the contour and color information of the carrier. In the proximity phase, when the structural features of the carrier become distinguishable, the lines forming a particular configuration are detected. Then, a similarity measurement criterion based on direction and distance constraints is exploited to perform line alignment between 3D lines and the detected 2D ones. Once the 2D-3D correspondences are identified, the rotation and translation are successively computed using the structural line constraints. Finally, the optimizer of the pose tracker is utilized to refine the pose for better accuracy. Experiments demonstrate that the proposed method achieve high pose estimation accuracy and real-time efficiency, which is suitable for guidance of autonomous landing.

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
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
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

Similar content being viewed by others

References

  1. Faessler, M., Mueggler, E., Schwabe, K., Scaramuzza, D.: A monocular pose estimation system based on infrared LEDs. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 907–913 (2014). https://doi.org/10.1109/ICRA.2014.6906962

  2. Sun, X., Zhou, J., Zhang, W., Wang, Z., Yu, Q.: Robust monocular pose tracking of less-distinct objects based on contour-part model. IEEE Trans. Circuits Syst. Video Technol. 31(11), 4409–4421 (2021). https://doi.org/10.1109/TCSVT.2021.3053696

    Article  Google Scholar 

  3. Stoiber, M., Pfanne, M., Strobl, K.H., Triebel, R., Albu-Schaffer, A.: SRT3D: a sparse region-based 3d object tracking approach for the real world. Int. J. Comput. Vision 130(4), 1008–1030 (2022). https://doi.org/10.1007/s11263-022-01579-8

    Article  Google Scholar 

  4. Akinlar, C., Topal, C.: EDlines: a real-time line segment detector with a false detection control. Pattern Recogn. Lett. 32(13), 1633–1642 (2011). https://doi.org/10.1016/j.patrec.2011.06.001

    Article  Google Scholar 

  5. Murray, R., Li, Z., Sastry, S.: A mathematical introduction to robot manipulation (2010). https://doi.org/10.1201/9781315136370

  6. Topal, C., Akınlar, C., Genc ̧, Y.: Edge drawing: a heuristic approach to robust real-time edge detection. In: 2010 20th International Conference on Pattern Recognition, pp. 2424–2427 (2010). https://doi.org/10.1109/ICPR.2010.593

  7. Desolneux, A., Moisan, L., Morel, J.M.: Meaningful alignments. Int. J. Comput. Vision 40, 7–23 (2000). https://doi.org/10.1023/A:1026593302236

    Article  Google Scholar 

  8. Grompone von Gioi, R., Jakubowicz, J., Morel, J.M., Randall, G.: LSD: a fast line segment detector with a false detection control. IEEE Trans. Pattern Anal. Mach. Intell. 32(4), 722–732 (2010). https://doi.org/10.1109/TPAMI.2008.300

  9. Wang, Q., Zhou, J., Li, Z., Sun, X., Yu, Q.: Robust and accurate monocular pose tracking for large pose shift. IEEE Trans. Industr. Electron. 70(8), 8163–8173 (2023). https://doi.org/10.1109/TIE.2022.3217598

    Article  Google Scholar 

  10. Elqursh, A., Elgammal, A.: Line-based relative pose estimation. In: CVPR 2011, pp. 3049–3056 (2011). https://doi.org/10.1109/CVPR.2011.5995512

  11. Community, B.O.: Blender - a 3d modelling and rendering package. http://www.blender.org. (2018)

    Google Scholar 

  12. Denninger, M., et al.: Blenderproc: reducing the reality gap with photorealistic rendering. In: International Conference on Robotics: Science and Systems, RSS 2020 (2020)

    Google Scholar 

Download references

Acknowledgement

This work was supported by the National Natural Science Foundation of China under Grant 12272404.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaoliang Sun .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 Chinese Society of Aeronautics and Astronautics

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, Q., Bi, D., Huang, H., Liu, J., Wang, Y., Sun, X. (2024). Airborne Monocular Vision Guidance Method for Autonomous Landing. In: Proceedings of the 6th China Aeronautical Science and Technology Conference. CASTC 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-8864-8_64

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-8864-8_64

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8863-1

  • Online ISBN: 978-981-99-8864-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics