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A 3-SPS-1S parallel robot-based laser sensing for applications in precision agriculture

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Abstract

A second green revolution is needed to double global food production over the next 30 years, and requires the use of the best of the technologies such as precision agriculture, to maximize production with minimum input costs and resources. This document shows advances in the development of prototype to direct acquired and sensing information to management fertilizes and water for applications in precision agriculture. We present the numerical/computational stage of such prototype which is equipped with laser sensors to determine the content of water, fertilizer or any other nutrient in row crops. Determining this information is key in order to know if the crop needs more of the above-mentioned substance. Our application is devoted for micro-crops which need to be swept with high precision as a result of its size. This agricultural problem translates to control engineering as a tracking problem.

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Notes

  1. Laser Inc. Technology, Laser measurement sensors. www.lasertech.com.

References

  • Bergvinson DJ, García-Lara S (2004) Genetic approaches to reducing losses of stored grain to insects and diseases. Curr Opin Plant Biol 7:480–485

    Article  Google Scholar 

  • Chaparro D, Zavala-Yoé R, Ramírez-Mendoza RA (2013) Kinematic and workspace analysis of a parallel robot used in security applications. In: IEEE 2013 international conference on mechatronics, electronics and automotive engineering (ICMEAE)

  • Chaparro D, Zavala-Yoé R, Ramírez-Mendoza RA (2014) Dynamics and control of a 3-SPS-1S parallel robot used in security applications. In: 21st international symposium on mathematical theory of networks and systems, MTNS

  • Cui G, Zhang Y (2009) Kinetostatic modeling and analysis of a new 3-DOF parallel manipulator. In: Proceedings on IEEE international conference on computational intelligence and software engineering, pp 1–4

  • Draiankov D et al (1996) Introduction to fuzzy control. Springer, Berlin

    Book  Google Scholar 

  • Hedley C (2015) The role of precision agriculture for improved nutrient management on farms. J Sci Food Agric 95:12–19

    Article  Google Scholar 

  • Merlet JP (2006) Parallel robots. Solid mechanics and its applications. Springer, Berlin

    Google Scholar 

  • Qamar JAK, Krishnan EV, Easawaran B (2010) Two-predator and two-pray species group defence model with switching effect. Int J Comput Biosci. doi:10.2316/J.2010.210-1003

  • Robertson J, Llewellyn RS, Mandel R, Lawes R, Bramley RVG, Swift L (2012) Adoption of variable rate fertiliser application in the Australian grains industry: status, issues and prospects. Precis Agric 13:181–199

    Article  Google Scholar 

  • Slotine JJ, Li W (1991) Applied nonlinear control. Prentice Hall, Upper Saddle River

    MATH  Google Scholar 

  • Srinivasan A (2006) Handbook of precision agriculture: principles and applications. Food Products, Binghamton, NY

    Google Scholar 

  • Torres A, Gómez A, Jiménez A (2015) Development of a multispectral system for precision agriculture applications using embedded devices. Sistemas y Telemática 13(33):27–44

    Article  Google Scholar 

  • Tsai K, Lin J (2006) Determining the compatible orientation workspace of Stewart–Gough parallel manipulators. Mech Mach Theory 41(10):1168–1184

    Article  MATH  Google Scholar 

  • Zavala-Yoe R (1997) Fuzzy control of second order vector systems: \(L_{2}\) stability. In: Proceedings of the 4th European control conference

  • Zavala-Yoé R (2008) Modelling and control of dynamical systems: numerical implementation in a behavioural framework. In: Studies in computational intelligence series, Springer. ISBN 978-3-540-78734-1

Download references

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Correspondence to Ricardo Zavala-Yoe.

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The authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Communicated by H. Ponce.

Appendix to derive Eq. (7)

Appendix to derive Eq. (7)

From Eq. (5), we obtain that \(\delta \mathbf{q}^{T}= \delta \mathbf{x}_{p} ^{T}\,\mathbf{J}_{p}^{T}\) and similarly, from Eq. (6), we get that \(\delta \mathbf{x}_{i}^{T}=\updelta \mathbf{x}_{p}^{T}\, \mathbf{J}_{i}^{T}\) and substituting the latter terms in \(\delta {{\varvec{q}}}^{T}\tau +\delta {{\varvec{x}}}_p {\hat{{\varvec{F}}}}_p +\sum {\delta {{\varvec{x}}} _i^{T}}{\hat{{\varvec{F}}}}_i =0\) we obtain that

$$\begin{aligned} \left( {\delta {{\varvec{x}}}_p^{T}\,{{\varvec{J}}}_p^{T}} \right) \tau +\delta {{\varvec{x}}}_p\, {\hat{{\varvec{F}}}}_p +\sum {\left( {\delta {{\varvec{x}}} _p^{T}\,{{\varvec{J}}}_i^{T}} \right) } {\hat{{\varvec{F}}}}_i =0 \\ \delta {{\varvec{x}}}_p^{T}\left( {{{\varvec{J}}}_p^{T}\tau +{\hat{{\varvec{F}}}}_p +\sum {{{\varvec{J}}}_i^{T}} {\hat{{\varvec{F}}}}_i } \right) =0 \end{aligned}$$

And from there, Eq. (7) follows from the virtual work principle.

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Zavala-Yoe, R., Ramírez-Mendoza, R.A. & García-Lara, S. A 3-SPS-1S parallel robot-based laser sensing for applications in precision agriculture. Soft Comput 21, 641–650 (2017). https://doi.org/10.1007/s00500-016-2457-7

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  • DOI: https://doi.org/10.1007/s00500-016-2457-7

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