Skip to main content
SpringerLink
Log in

Trajectory-Planning Algorithm Based on Engineering Vision in Manipulator Management

  • Published:
Russian Engineering Research Aims and scope

Abstract

A long-range optical device and an engineering-vision system are used to relate the coordinate systems of the workpiece and tool to the basic coordinate system of a manipulator. The deficiencies of the long-range optical sensor limit its use with objects that are highly reflective and are characterized by surface scattering, on account of the multiplicity of beam paths. An algorithm is proposed for trajectory planning on the basis of a three-dimensional model of the workpiece. That decreases the scanning time, without loss of model quality.

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.

Similar content being viewed by others

REFERENCES

  1. Dorozhkin, I.N., Dorozhkina, O.K., and Shinkevich, I.A., Digital production introduction at the expense of industrial and operational management automation at the industrial enterprise, Vestn. Mosk. Gos. Tekhnol. Univ., Stankin, 2018, no. 2, pp. 112–116.

  2. Moroz, A.Yu., Rodionova, A.V., and Skhirtladze, A.G., Cost reduction on snap-in design-technological preparation of production engineering products, Vestn. Mosk. Gos. Tekhnol. Univ., Stankin, 2017, no. 3, pp. 110–113.

  3. Voronenko, V.P., Sedykh, M.I., and Kuzyakhmetova, A.V., Classification of losses of working time in engineering production and the reasons for their occurrence, Vestn. Mosk. Gos. Tekhnol. Univ., Stankin, 2018, no. 1, pp. 61–65.

  4. Zelenskii, A.A. and Pis’menskova, M.M., The human action recognition method on complex-structured images and stochastic texture background, Vestn. Mosk. Gos. Tekhnol. Univ., Stankin, 2018, no. 3, pp. 116–120.

  5. Zhang, Z., Microsoft kinect sensor and its effect, IEEE Multimedia, 2012, vol. 19, no. 2, pp. 4–10.

    Article  Google Scholar 

  6. Shi, J., Dong, Y., and Su, H., Learning non-Lambertian object intrinsics across ShapeNet categories, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Piscataway, NJ: Inst. Electr. Electron. Eng., 2017, pp. 1685–1694.

  7. Chollet, F., Deep Learning mit Python und Keras: Das Praxis-Handbuch vom Entwickler der Keras-Bibliothek, Frechen: MITP-Verlag, 2018.

  8. Goodfellow, I., Fischer, F., and Brox, T., Generative adversarial nets, Proc. Annual Conf. on Neural Information Processing Systems “Advances in Neural Information Processing Systems,” Montreal, 2014, pp. 2672–2680.

  9. Ronneberger, O., Fischer, F., and Brox, T., Convolutional networks for biomedical image segmentation, Proc. 18th Int. Conf. “Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015),” Munich, Berlin: Springer-Verlag, 2015, pp. 234–241.

  10. Zelenskii, A.A. and Frants, V.A., Generative adversarial neural networks for video feature extraction in task of visual quality assessment, Vestn. Mosk. Gos. Tekhnol. Univ., Stankin, 2018, no. 3, pp. 86–90.

  11. Zelensky, A.A., Voronin, V., Semenishchev, E., et al., Video content verification using blockchain technology, Proc. IEEE Int. Conf. on Smart Cloud, Piscataway, NJ: Inst. Electr. Electron. Eng., 2018, pp. 208–212.

Download references

Author information

Authors and Affiliations

  1. Moscow State Technical University “Stankin”, 127055, Moscow, Russia

    A. A. Zelenskii, V. A. Frants & E. A. Semenishchev

Authors
  1. A. A. Zelenskii
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. A. Frants
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. A. Semenishchev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. A. Frants.

Additional information

Translated by B. Gilbert

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zelenskii, A.A., Frants, V.A. & Semenishchev, E.A. Trajectory-Planning Algorithm Based on Engineering Vision in Manipulator Management. Russ. Engin. Res. 40, 1–5 (2020). https://doi.org/10.3103/S1068798X20010268

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S1068798X20010268

Keywords:

Search

Navigation