Skip to main content

Automated Tool Trajectory Planning for Spray Painting Robot of Free-Form Surfaces

  • Conference paper
  • First Online:
Frontier Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 375))

Abstract

Automated spray painting is an important process in the manufacturing of many products. In order to ensure computational efficiency, a new tool trajectory optimization scheme based on T-Bézier curve is developed. And a T-Bézier basis is presented in trajectory optimization problem. The tool trajectory is formed through offsetting the distance between spray gun and the free-form surface along the normal vectors. Automotive body parts, which are free-form surfaces, are used to test the scheme. The results of experiments have shown that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
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

Institutional subscriptions

References

  1. Conner DC, Greenfield A, Atkar PN et al (2005) Paint deposition modeling for trajectory planning on automotive surfaces. IEEE Trans Autom Sci Eng 2(4):381–392

    Article  Google Scholar 

  2. Antonio JK, Ramabhadran R, Ling TL (1997) A framework for trajectory planning for automated spray coating. Int J Robot Autom 12(4):124–134

    Google Scholar 

  3. Chen HP, Xi N, Sheng W et al (2005) Optimizing material distribution for tool trajectory generation in surface manufacturing. In: Proceedings of the 2005 IEEE/ASME international conference on advanced intelligent mechatronics, pp 1389–1394

    Google Scholar 

  4. Xia W, Wei CH, Liao XP (2009) Surface segmentation based intelligent trajectory planning and control modeling for spray painting. In: Proceeding of the 2009 IEEE international conference on mechatronics and automation, China, Changchun, pp 4958–4963

    Google Scholar 

  5. From PJ, Gunnar J, Gravdahl JT (2011) Optimal paint gun orientation in spray paint applications—experimental results. IEEE Trans Autom Sci Eng 8(2):438–442

    Article  Google Scholar 

  6. Chen HP, Fuhlbrigge T (2008) Automated industrial robot path planning for spray painting process: a review. In: 4th IEEE conference on automation science and engineering, USA, Washington DC, pp 522–527

    Google Scholar 

  7. Chen W, Zhao DA (2013) Path planning for spray painting robot of workpiece surfaces. Math Probl Eng 2013(8). doi:10.1155/2013/659457

    Google Scholar 

  8. Chen HP, Sheng WH (2011) Transformative industrial robot programming in surface manufacturing. In: 2011 IEEE international conference on robots and automation, China, Shanghai, pp 6059–6064

    Google Scholar 

  9. Sheng WH, Chen HP, Xi N, Tan JD (2004) Optimal tool path planning for compound surfaces in spray forming processes. In: IEEE international conference on robotics and automation, USA, New Orleans, pp 45–50

    Google Scholar 

  10. Yu SR, Cao LG (2011) Modeling and prediction of paint film deposition rate for robotic spray painting. In: Proceedings of the 2011 IEEE international conference on macaronis and automation, China, Beijing, pp 1445–1450

    Google Scholar 

  11. Gasparetto A (2012) Automatic path and trajectory planning for robotic spray painting. In: 7th German conference on robotics, German, Munich, pp 211–216

    Google Scholar 

  12. Li XZ, Landsnes OA, Chen HP (2010) Automatic trajectory generation for robotic painting application. In: 41st International symposium on robotics and 2010 6th German conference on robotics, German, Berlin, pp 1–6

    Google Scholar 

  13. Li FA, Zhao DA, Xie GH (2009) Trajectory optimization of spray painting robot based on adapted genetic algorithm. In: International conference on measuring technology and mechatronics automation, ICMTMA 2009, China, Changsha, pp 907–910

    Google Scholar 

  14. Chen W, Zhao DA (2009) Tool trajectory optimization of robotic spray painting. In: IEEE International conference on intelligent computation technology and automation, China, ChangSha, pp 419–422

    Google Scholar 

  15. Juhász M, Ágoston R (2013) A class of generalized B-spline curves. Comput Aided Geom Des 30(1):85–115

    Article  MathSciNet  MATH  Google Scholar 

  16. Mainar E, Peña JM (2002) A basis of C-Bézier splines with optimal properties. Comput Aided Geom Des 19(10):291–295

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This project is supported by University Science Foundation of Jiangsu province in China (Grant no. 14KJB510008), Senior talent Research Foundation of Jiangsu University (Grant no. 5503000046), Doctoral Scientific Research Foundation of Jiangsu University of science and technology (Grant No. 635031306) and National Natural Science Foundation Advance Research Project for Jiangsu University of science and technology (Grant No. 633031306)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this paper

Cite this paper

Chen, W., Tang, Y. (2016). Automated Tool Trajectory Planning for Spray Painting Robot of Free-Form Surfaces. In: Hung, J., Yen, N., Li, KC. (eds) Frontier Computing. Lecture Notes in Electrical Engineering, vol 375. Springer, Singapore. https://doi.org/10.1007/978-981-10-0539-8_78

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-0539-8_78

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0538-1

  • Online ISBN: 978-981-10-0539-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics