SYSTEM ANALYSIS OF A GROUND ROBOTIC PLATFORM FOR AGRICULTURAL PURPOSE

Abstract

The aim of this work is to conduct a systemic analysis of mobile robotic platforms that can be used in agriculture for cargo transportation and weed control. This study is relevant due to the increasing population, decreasing arable land, natural population outflow from rural areas, and reduction in agricultural machinery. To achieve the set goal, a "tree" of objectives for the systemic analysis of the constructive implementation of platforms has been formed, which precedes and decomposes the stages of designing and developing agricultural robots. Due to the presence of fuzzy and verbal evaluation indicators by experts of robotic platforms, the authors suggest defining them in the form of fuzzy intervals, which, with the use of additive convolution, allow obtaining a composite indicator that can be presented either in fuzzy form or in the form of pessimistic, optimistic, or neutral assessments. At the same time, the weighting coefficients of additive convolution can also be presented in fuzzy form. For this purpose, operations of multiplication and addition of fuzzy intervals are proposed. To conduct simulation modeling, the structure of software is presented using an object-oriented approach. By overloading classical addition and multiplication operations, it was possible to implement algebraic operations with fuzzy intervals without complicating calculations. The modeling results confirmed the feasibility of the approach and allowed determining the constructive implementation, layout, engines, and actuators for the agricultural platform. The proposed methods can be used before the stages of designing and developing robots for various purposes, and the use of indicators in fuzzy form allows reducing the burden on experts.

Authors

References

1. Zagazezheva O.Z., Berbekova M.M. Osnovnye trendy razvitiya robotizirovannykh tekhnologiy v
sel'skom khozyaystve [Main trends in the development of robotic technologies in agriculture],
Izvestiya KBNTS RAN [News of the KBSC RAS], 2021, No. 5 (103)m pp. 11-20.
2. Solov'ev V.V., Shadrina V.V., Nomerchuk A.Ya., Filatov R.K. Perspektivy razvitiya
sel'skokhozyaystvennoy robototekhniki v usloviyakh importozameshcheniya [Prospects for the development
of agricultural robotics in the conditions of import substitution ], Sb. trudov XIII Vserossiyskoy
SHkoly-seminara, molodykh uchenykh, aspirantov, studentov i shkol'nikov [Collection of works of the
XIII All-Russian School-Seminar, young scientists, graduate students, students and schoolchildren].
Rostov-on-Don – Taganrog: YuFU, 2022, pp. 27-34.
3. Santos Valle, S. and Kienzle. Agriculture 4.0 - Agricultural robotics and automated equipment for
sustainable crop production, Integrated Crop Management. Rome, 2020, Vol. 24.
4. Izmaylov A.Yu., Smirnov I.G., Khort D.O. Tsifrovye agrotekhnologii v sisteme «Umnyy sad» [Digital
agricultural technologies in the “Smart Garden” system], Sadovodstvo i vinogradarstvo [Gardening
and viticulture], 2018, 6, pp. 33-39. DOI: 10.31676/0235-2591-2018-6-33-39.
5. Oliveira L.F., Moreira A.P., & Silva M.S. Advances in Agriculture Robotics: A State-of-the-Art Review
and Challenges Ahead, Robotics, 2021, 10, 52 p.
6. Higuti Vitor & Velasquez Andres & agalhães Daniel & Becker arcelo & Chowdhary Girish. Under
canopy light detection and ranging‐based autonomous navigation, Journal of Field Robotics, 2018,
No. 36, 10.1002/rob.21852.
7. Adamides George. Agricultural Robots in Targeted Spraying: A mini State-of-the-Art review, Robotics
& Automation Engineering Journal, 2017, No. 2. 10.19080/RAEJ.2018.02.555581.
8. Emmi Luis & Gonzalez-de-Soto Mariano & Pajares Gonzalo & Gonzalez-de-Santos Pablo. New
Trends in Robotics for Agriculture: Integration and Assessment of a Real Fleet of Robots, The
ScientificWorld Journal, 2014, 404059. 10.1155/2014/404059.
9. Corpe Samuel & Tang Liqiong & Abplanalp Phillip. GPS-guided modular design mobile robot platform
for agricultural applications, Proceedings of the International Conference on Sensing Technology,
ICST, 2013, pp. 806-810. 10.1109/ICSensT.2013.6727763.
10. Chebrolu Nived & Lottes Philipp & Schaefer Alexander & Winterhalter Wera & Burgard Wolfram &
Stachniss Cyrill. Agricultural robot dataset for plant classification, localization and mapping on sugar beet
fields, The International Journal of Robotics Research, 2017, No. 36. 10.1177/0278364917720510.
11. Tabile Rubens & Godoy Eduardo & Pereira Robson & Tangerino Giovana & Porto Arthur & Inamasu
Ricardo. Design and development of the architecture of an agricultural mobile robot,
Engenharia Agrícola, 2011, No. 31, pp. 130-142. 10.1590/S0100-69162011000100013.
12. Bawden Owen, Ball David, Kulk Jason, Perez Tristan, & Russell Raymond. A lightweight, modular
robotic vehicle for the sustainable intensification of agriculture, In Chen, C (Ed.), Proceedings of the
16th Australasian Conference on Robotics and Automation 2014. Australian Robotics and Automation
Association (ARAA), Australia, pp. 1-9.
13. Abhishesh P. et al. Multipurpose Agricultural Robot Platform: Conceptual Design of Control System
Software for Autonomous Driving and Agricultural Operations Using Programmable Logic Controller,
World Academy of Science, Engineering and Technology, International Journal of Agricultural and
Biosystems Engineering, 2017, 4.
14. Pecka Aldis & Osadcuks Vitalijs. Conceptual design of modular multi functional agricultural mobile
robot, 2018, pp. 202-206. 10.22616/rrd.24.2018.031.
15. Nielsen S.H., Jensen K., Bøgild A., Jørgensen O.J., Jacobsen N.J., Jæger C.L.D., Jørgensen . N.
A Low Cost, Modular Robotics Tool Carrier For Precision Agriculture Research, 11th International
Conference on Precision Agriculture International Society of Precision Agriculture, 2012.
16. Chernyak Yu.I. Sistemnyy analiz v upravlenii ekonomikoy [System analysis in economic management].
Moscow: Ekonomika, 1975, 193 p.
17. Finaev V.I. Modeli sistem prinyatiya resheniy: ucheb. posobie [Models of decision-making systems:
textbook]. Taganrog: Izd-vo TRTU, 2005, 118 p.
18. Shtoyer R. Mnogokriterial'naya optimizatsiya [Multicriteria optimization]: trans. from engl. Moscow:
Radio i svyaz', 1992, 504 p.
19. Lotov A.V., Pospelova I.I. Mnogokriterial'nye zadachi prinyatiya resheniy: ucheb. posobie
[Multicriteria decision-making problems: textbook]. Moscow: MAKS Press, 2008, 197 p.
20. Dmitriev M.G., Lomazov V.A. Otsenka chuvstvitel'nosti lineynoy svertki chastnykh kriteriev pri
ekspertnom opredelenii vesovykh koeffitsientov [Assessing the sensitivity of linear convolution of
partial criteria in the expert determination of weighting coefficients], Iskusstvennyy intellekt i prinyatie
resheniy [Artificial intelligence and decision making], 2014, No. 1, pp. 52-56. ISSN: 2071-8594.
21. Solov'ev V.V. Algoritm otsenki effektivnosti funktsionirovaniya slozhnykh tekhnicheskikh sistem
[Algorithm for assessing the effectiveness of the functioning of complex technical systems], Mater.
Vserossiyskoy nauchnoy konferentsii: Perspektivy razvitiya gumanitarnykh i tekhnicheskikh system
[Materials of the All-Russian Scientific Conference: Prospects for the development of humanitarian
and technical systems]: in 3 part. Part 2. Taganrog: Izd-vo TTI YuFU, 2011, pp. 61-62.

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Published:

2024-05-28

Issue:

Section:

SECTION I. CONTROL SYSTEMS AND MODELING

Keywords:

Robotic platform, systemic analysis, additive convolution, fuzzy interval, construction assessment