https://doi.org/10.4081/jae.2021.1144
Study of the steering of a wide span vehicle controlled by a local positioning system
Published: 30 September 2021
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Controlled traffic farming allows to minimize traffic-induced soil compaction by a permanent separation of the crop zone from the traffic lanes used by wide span tractors. The Authors developed an agricultural wide span vehicle equipped with a skid equipment for turning and an automatic driving system prototype based on a laser beam. The aim of this work was to study the kinematic conditions that control the steering of this machine. Furthermore, the accuracy and the maximum delay time of the signal transmission by the automatic driving system of the set-up was also assessed. In comparison with crawler tractors, the turning of the agricultural wide span vehicle needs a smaller difference in the moments applied to its right- and left-side wheels. For the predetermined accuracy of the beam position relative to the plant rows, ±ds = ±0.025 m, the accuracy of the direction of the laser beam at a distance S=200 m should not be more than ±0.07° and ±0.0014°, considering a run length of 1000 m. Furthermore, at a speed V=2.5 m s–1 a trajectory deviation φ≤5° requires a topmost delay time of the control signal of Δtmax=0.11 s is required.
Abe M. 2015. Vehicle handling dynamics. 2nd ed. Elsevier Ltd., Oxford, UK.
DOI: https://doi.org/10.1016/B978-0-08-100390-9.00011-7
Bakker T., Van A.K., Bontsema J. 2011. Autonomous navigation using a robot platform in a sugar beet field. Biosyst. Eng. 109:357-68.
DOI: https://doi.org/10.1016/j.biosystemseng.2011.05.001
Bulgakov V., Pascuzzi S., Adamchuk V., Ivanovs S., Pylypaka S. 2019a. A theoretical study of the limit path of the movement of a layer of soil along the plough mouldboard. Soil Tillage Res. 195:104406.
DOI: https://doi.org/10.1016/j.still.2019.104406
Bulgakov V., Pascuzzi S., Adamchuk V., Kuvachov V., Nozdrovicky L. 2019b. Theoretical study of transverse offsets of wide span tractor working implements and their influence on damage to row crops. Agriculture (Switzerland), 9:144.
DOI: https://doi.org/10.3390/agriculture9070144
Bulgakov V., Pascuzzi S., Anifantis A.S., Santoro F. 2019c. Oscillations analysis of front-mounted beet topper machine for biomass harvesting. Energies. 12:2774.
DOI: https://doi.org/10.3390/en12142774
Bulgakov V., Pascuzzi S., Ivanovs S., Nadykto V., Nowak, J. 2020. Kinematic discrepancy between driving wheels evaluated for a modular traction device. Biosyst. Eng. 196:88-96.
DOI: https://doi.org/10.1016/j.biosystemseng.2020.05.017
Bulgakov V., Pascuzzi S., Nadykto V., Ivanovs, S. 2018. A mathematical model of the plane-parallel movement of an asymmetric machine-and-tractor aggregate. Agriculture (Switzerland), 8:151.
DOI: https://doi.org/10.3390/agriculture8100151
Chamen W.C.T. 1992. Assessment of a wide span vehicle (Gantry), and soil and cereal crop responses to its use in a zero traffic regime. Soil Tillage Res. 24:359-80.
DOI: https://doi.org/10.1016/0167-1987(92)90119-V
Chebrolu N., Lottes P., Schaefe A., Winterhalter W., Burgard W., Stachniss C. 2017. Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields. Int. J. Rob. Res. 36:1045-52.
DOI: https://doi.org/10.1177/0278364917720510
Griepentrog H.W. 2009. Safe and reliable: Further development of a field robot. Prec. Agric. 9:857-66.
Hamza M.A., Anderson W.K. 2005. Soil compaction in cropping systems - a review of the nature, causes and possible solutions. Soil Tillage Res. 82:121-45.
DOI: https://doi.org/10.1016/j.still.2004.08.009
He B., Liu G., Ji Y. 2011. Auto recognition of navigation path for harvest robot based on machine vision. Computer Comput. Technol. Agric. 4:138-48.
DOI: https://doi.org/10.1007/978-3-642-18333-1_19
ISO, 2008. Agricultural tractors - Requirements for steering. Norm ISO 10998:2008. International for Standardization Publ., Geneva, Switzerland.
Yang L., Luo T., Cheng X., Li J., Song Y. 2015. Universal autopilot system of tractor based on Raspberry Pi. Trans. Chinese Soc. Agricult. Engine. 31:109-15.
Ji C., Zhou J. 2014. Current situation of navigation technologies for agricultural machinery. Trans. Chinese Soc. Agricult. Engine. 45:44-54.
Keller T., Sandin M., Colombi T., Horn R, Or D. 2019. Historical increase in agricultural machinery weights enhanced soil stress levels and adversely affected soil functioning. Soil Tillage Res. 194:104293.
DOI: https://doi.org/10.1016/j.still.2019.104293
Luo X., Zhang Z., Zhao Z., Chen B., Hu L., Wu X. 2009. Design of DGPS navigation control system for Dongfanghong X-804 tractor. Trans. Chinese Soc. Agricult. Engine. 25:139-45.
Onal I. 2012. Controlled traffic farming and wide span tractors. J. Agricult. Machine. Sci. 8:353-64.
Park K., 2018. Fundamentals of probability and stochastic processes with applications to communications. Springer, Berlin, Germany.
DOI: https://doi.org/10.1007/978-3-319-68075-0_8
Raper R.L. 2005. Agricultural traffic impacts on soil. J. Terramechan. 42:259-80.
DOI: https://doi.org/10.1016/j.jterra.2004.10.010
Wong J.Y. 2001. Theory of ground vehicle. 3rd ed. J. Wiley & Sons, New York, NY, USA.
Zhu Q., Gao G., Niu W. 2016. The automatic navigation driving system of agricultural machinery. Modern Agric. 5:5-67.
How to Cite
Bulgakov, V. (2021) “Study of the steering of a wide span vehicle controlled by a local positioning system”, Journal of Agricultural Engineering, 52(3). doi: 10.4081/jae.2021.1144.
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