Skip to main content
SpringerLink
Log in
Book cover

Machine Vision and Navigation pp 321–345Cite as

Optimal Generation of Closed Trajectories over Large, Arbitrary Surfaces Based on Non-calibrated Vision

  • Chapter
  • First Online:

  • 1800 Accesses

Abstract

This chapter presents a methodology for the accurate generation and tracking of closed trajectories over arbitrary, large surfaces of unknown geometry, using a robot whose control is based on the use of a non-calibrated vision system. This capability can be applied to relevant industrial robotic maneuvers, like the welding or cutting of commercially-available metal plates. The proposed technique is based on a calibration-free, vision-based robot control methodology referred to as camera-space manipulation. This is combined with a geodesic-mapping approach, with the purpose of generating and tracking a trajectory stored as a CAD model, over an arbitrarily curved surface, along a user-defined position and orientation. In the context of applications to large surfaces, the maneuver precision of the positioning and path-tracking tasks depend on several aspects like camera resolution and mapping procedure, which has the potential of introducing distortion, especially in non-developable surfaces. In terms of the mapping procedure, this chapter discusses two options, referred to as modified geodesic mapping and virtual-projection mapping. A measure used to diminish the distortion caused by the mapping procedure and a technique for achieving closure of a given closed-path, when this is tracked over large, non-developable surfaces, are presented herein. The performance of the proposed methodology was evaluated using an industrial robot with a large workspace, combined with structured lighting used to reduce the complexity of the image analysis process.

This is a preview of subscription content, 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   229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   299.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

References

  1. Bronshtein, I. N., Semendyayev, K. A., Musiol, G., & Muehlig, H. (2007). Handbook of mathematics (5th ed.). Berlin: Springer.

    MATH  Google Scholar 

  2. Deng, X., Zhang, Z., Sintov, A., Huang, J., & Bretl, T. (2018). Feature-constrained active visual SLAM for mobile robot navigation. In IEEE International Conference on Robotics and Automation (ICRA), May 2018 (pp. 7233–7238).

    Google Scholar 

  3. Gonzáalez-Gálvan, E. J., Cruz-Ramírez, S. R., Seelinger, M. J., & Cervantes-Sanchez, J. J. (2003). An efficient multi-camera, multi-target scheme for the three-dimensional control of robots using uncalibrated vision. Robotics and Computer-Integrated Manufacturing, 19(5), 387–400.

    Article  Google Scholar 

  4. González-Gálvan, E. J., Loredo-Flores, A., Pazos-Flores, F., & Cervantes-Sánchez, J. (2005). An optimal path-tracking algorithm for unstructured environment based on uncalibrated vision. In IEEE International Conference on Robotics and Automation, April 2005 (pp. 2547–2552).

    Google Scholar 

  5. González-Gálvan, E. J., Loredo-Flores, A., Cervantes-Sánchez, J. J., Aguilera-Cortés, L. A., & Skaar, S. B. (2008). An optimal path-generation algorithm for surface manufacturing of arbitrarily curved surfaces using uncalibrated vision. Robotics and Computer-Integrated Manufacturing, 24(1), 77–91.

    Article  Google Scholar 

  6. González-Gálvan, E. J., Chavez, C. A., Bonilla, I., Mendoza, M., Raygoza, L. A., Loredo Flores, A., et al. (2011). Precise industrial robot positioning and path-tracking over large surfaces using non-calibrated vision. In IEEE International Conference on Robotics and Automation, May 2011 (pp. 5160–5166).

    Google Scholar 

  7. Ivanov, M., Lindner, L., Sergiyenko, O., Rodríguez-Quin̄onez, J. C., Flores-Fuentes, W., & Rivas-Lopez, M. (2019). Mobile robot path planning using continuous laser scanning. In Optoelectronics in machine vision-based theories and applications (pp. 338–372). Hershey: IGI Global.

    Google Scholar 

  8. Kalla, P., Koona, R., Ravindranath, P., & Sudhakar, I. (2018). Coordinate reference frame technique for robotic planar path planning. Materials Today: Proceedings, 5(9), Part 3, 19073–19079.

    Google Scholar 

  9. Lindner, L., Sergiyenko, O., Rodríguez-Quin̄onez, J. C., Rivas-Lopez, M., Hernandez-Balbuena, D., Flores-Fuentes, W., et al. (2016). Mobile robot vision system using continuous laser scanning for industrial application. Industrial Robot: An International Journal, 43(4), 360–369.

    Google Scholar 

  10. Lu, B., Chu, H. K., Huang, K. C., & Cheng, L. (2018). Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing. IEEE Transactions on Automation Science and Engineering, 16(2), 542–556.

    Article  Google Scholar 

  11. McInerney, A. (2013). First steps in differential geometry: Riemannian, contact, symplectic. Undergraduate texts in mathematics. New York: Springer.

    Book  Google Scholar 

  12. Mouaddib, E. M., Sagawa, R., Echigo, T., & Yagi, Y. (2005). Stereovision with a single camera and multiple mirror. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation (pp. 800–805).

    Google Scholar 

  13. Moura, J., McColl, W., Taykaldiranian, G., Tomiyama, T., & Erden, M. S. (2018). Automation of train cab front cleaning with a robot manipulator. IEEE Robotics and Automation Letters, 3(4), 3058–3065.

    Article  Google Scholar 

  14. O’Gorman, L., Sammon, M. J., & Seul, M. (2008). Practical algorithms for image analysis: Description, examples programs and projects (2nd ed.). Cambridge: Cambridge University Press.

    MATH  Google Scholar 

  15. O’Neill, B. (2006). Elementary differential geometry (Revised 2nd ed.). Cambridge/Amsterdam: Academic/Elsevier.

    MATH  Google Scholar 

  16. Palenta, K., & Babiarz, A. (2014). KUKA robot motion planning using the 1742 smart camera. In A. Guca et al. (Eds.), Man-Machine Interactions 3. Advances in intelligent systems and computing (Vol. 242, pp. 115–122). Basil: Springer.

    Google Scholar 

  17. Perrollaz, M., Khorbotly, S., Cool, A., Yoder, J.-D., & Baumgartner, E. (2012). Teachless teach-repeat: Toward vision-based programming of industrial robots. In Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA), May 2012 (pp. 409,414, 14–18).

    Google Scholar 

  18. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (2007). Numerical recipes: The art of scientific computing (3rd ed.). Cambridge: Cambridge University Press.

    MATH  Google Scholar 

  19. Raygoza-Perez, L. A., González-Gálvan, E. J., Loredo-Flores, A., Pastor, J. J., & Baumgartner, E. (2010). An enabling vision-based approach for non-calibrated, robot positioning task. International Review of Automatic Control. Theory and Applications, 3(6), 710–722.

    Google Scholar 

  20. Robinson, M. L. (2001). A structured lighting approach to image analysis for robotic applications using camera-space manipulation (Ph.D. Dissertation, University of Notre Dame)

    Google Scholar 

  21. Rodríuez-Quin̄onez, J. C., Sergiyenko, O., Flores-Fuentes, W., Rivas-lopez, M., Hernandez-Balbuena, D., Rascón, R., et al. (2017). Improve a 3D distance measurement accuracy in stereo vision systems using optimization methods’ approach. Opto-Electronics Review, 25(1), 24–32.

    Google Scholar 

  22. Real, O. R., Castro-Toscano, M. J., Rodríguez-Quin̄onez, J. C., Serginyenko, O., Hernández-Balbuena, D., Rivas-Lopez, M., et al. (2019) Surface measurement techniques in machine vision: Operation, applications, and trends. In Optoelectronics in machine vision-based theories and applications (pp. 79–104). Hershey: IGI Global.

    Google Scholar 

  23. Russ, J. C. (2007). The image processing handbook (5th ed.). Boca Raton: CRC Press.

    MATH  Google Scholar 

  24. Seelinger, M., Gonzalez-Galvan, E., Robinson, M., & Skaar, S. B. (1998). Towards a robotic plasma spraying operation using vision. IEEE Robotics and Automation (Special Issue on Visual Servoing), 5(4), 33–36.

    Article  Google Scholar 

  25. Senior, A. W., & Hampapur, M. L. (2005). Acquiring multi-scale images by Pan-Tilt-Zoom control and automatic multi-camera calibration. In Proceedings of the Seventh IEEE Workshop on Applications of Computer Vision (WACV/MOTION’05) (pp. 1–6).

    Google Scholar 

  26. Song, K.-T., & Tai, J.-C. (2006). Dynamic calibration of Pan-Tilt-Zoom cameras for traffic monitoring. IEEE Transactions on Systems, Man and Cybernetics, 36(5), 1091–1103.

    Article  Google Scholar 

  27. Stïcker, D. (1999). Elementary geometric methods: Line segment intersection and inclusion in a polygon. Technical Report, Department of Computer Science, University of Oldenburg.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Autonomous University of San Luis Potosi (UASLP), San Luis Potosi, SLP, Mexico

    Emilio J. Gonzalez-Galvan, Ambrocio Loredo-Flores, Isela Bonilla-Gutierrez & Marco O. Mendoza-Gutierrez

  2. Campus Sur, UAA, Av. Universidad 940. Aguascalientes, AGS, Mexico

    Cesar Chavez-Olivares

  3. Centro de Ciencias Basicas, UAA, Av. Universidad 940. Aguascalientes, AGS, Mexico

    Luis A. Raygoza

  4. SLP Campus, ITESM, Eugenio Garza Sada 300, San Luis Potosi, SLP, Mexico

    Sergio Rolando Cruz-Ramírez

Authors
  1. Emilio J. Gonzalez-Galvan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ambrocio Loredo-Flores
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Isela Bonilla-Gutierrez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marco O. Mendoza-Gutierrez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cesar Chavez-Olivares
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Luis A. Raygoza
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sergio Rolando Cruz-Ramírez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emilio J. Gonzalez-Galvan .

Editor information

Editors and Affiliations

  1. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Oleg Sergiyenko

  2. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Wendy Flores-Fuentes

  3. Leuphana University of Lueneburg, Lueneburg, Low Saxony, Niedersachsen, Germany

    Paolo Mercorelli

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gonzalez-Galvan, E.J. et al. (2020). Optimal Generation of Closed Trajectories over Large, Arbitrary Surfaces Based on Non-calibrated Vision. In: Sergiyenko, O., Flores-Fuentes, W., Mercorelli, P. (eds) Machine Vision and Navigation. Springer, Cham. https://doi.org/10.1007/978-3-030-22587-2_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-22587-2_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22586-5

  • Online ISBN: 978-3-030-22587-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation