https://doi.org/10.4081/jae.2023.1355
0
0
0
0
Smart Citations0
0
0
0
Citing PublicationsSupportingMentioningContrasting
See how this article has been cited at scite.ai
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Automatic travelling of agricultural support robot for a fruit farm. Verification of effectiveness of real-time kinematic-global navigation satellite system and developed a simulator for specification design
Labour shortages and fatal accidents in agricultural work have recently emerged as critical problems in Japan, necessitating productivity enhancement, workload reduction, and safety assurance. Therefore, in Japan and countries with similar agricultural environments, the use of small and inexpensive agricultural robots that can be employed in mountain farms and orchards is desirable. In this study, a dynamic positioning test was performed in orchards in a mountainous region to verify the positioning accuracy and stability of the global navigation satellite system (GNSS) and realtime kinematic (RTK)-GNSS. In addition, a simulator for an agricultural robot that could consider the environmental information of orchards was developed, and driving tests were conducted using the GNSS data acquired in the simulation. The error of the GNSS module was set to be higher than that for the measured value, and the robot travelling in the orchard was simulated. The results of GNSS positioning tests in an orchard near a mountainous area indicate that in the specific environmental conditions, the RTK-GNSS and stand-alone (SA)-GNSS can attain a positioning accuracy with an order of tens of centimetres and few metres, respectively. Moreover, the simulation results based on the GNSS positioning results indicate that a vehicle implementing RTK-GNSS and a simple obstacle detection sensor can travel autonomously in a farmyard without colliding with the tree rows. In contrast, a vehicle implementing SA-GNSS and a simple obstacle detection sensor cannot drive autonomously in an orchard and must realise selfpositioning using a more accurate sensor. Therefore, the proposed approach of realising simulations of autonomous agricultural robots based on GNSS data from a real orchard can facilitate the evaluation of practical agricultural robots and confirm safe travelling roots. Furthermore, the results demonstrate the possibility of developing small agricultural robots for orchards. We conducted the GNSS positioning test in an orchard at an altitude of approximately 830 m. A similar performance can be expected under alike agricultural situations because the error of the GNSS module was set to be higher than the measured value in the driving simulation test.
Allred, B., Wishart, D., Martinez, L., Schomberg, H., Mirsky, S., Meyers, G., Elliott, J., & Charyton, C. (2018). Delineation of agricultural drainage pipe patterns using ground penetrating radar integrated with a real-time kinematic global navigation satellite system. Agriculture, 8(11). https://doi.org/10.3390/agriculture8110167
DOI: https://doi.org/10.3390/agriculture8110167
Alkan, R. M., Erol, S., İlçi, V., & Ozulu, M. (2020). Comparative analysis of real-time kinematic and PPP techniques in dynamic environment. Measurement: Journal of the International Measurement Confederation, 163, 107995. https://doi.org/10.1016/j.measurement.2020.107995
DOI: https://doi.org/10.1016/j.measurement.2020.107995
Barawid Jr., C. O. & Noguchi, N. (2008). Automatic guidance system in real-time orchard application (Part 1). Journal of the Japanese Society of Agricultural Machinery, 70(6), 76–84. https://www.jstage.jst.go.jp/article/jsam1937/70/6/70_76/_pdf/-char/en
Barawid Jr., C. O. & Noguchi, N. (2010). Automatic guidance system in real-time orchard application (Part 2). Journal of the Japanese Society of Agricultural Machinery, 72(3), 243–250. https://www.jstage.jst.go.jp/article/jsam/72/3/72_243/_article/-char/ja
Blok, P. M., Boheemen, K., V., Evert, F. K., V., IJsselmuiden, J., & Kim, G. H. (2019). Robot navigation in orchards with localization based on Particle filter and Kalman filter. Computers and Electronics in Agriculture, 157, 261–269. https://doi.org/10.1016/j.compag.2018.12.046
DOI: https://doi.org/10.1016/j.compag.2018.12.046
Catania, P., Comparetti, A., Febo, P., Morello, G., Orlando, S., Roma, E., & Vallone, M. (2020). Positioning accuracy comparison of GNSS receivers used for mapping and guidance of agricultural machines. Agronomy, 10(7). https://doi.org/10.3390/agronomy10070924
DOI: https://doi.org/10.3390/agronomy10070924
Cheein, F. A., Steiner, G., Paina, G. P., & Carelli, R. (2011). Optimized EIF-SLAM algorithm for precision agriculture mapping based on stems detection. Computers and Electronics in Agriculture, 78(2), 195-207. https://doi.org/10.1155/2019/4687819
DOI: https://doi.org/10.1016/j.compag.2011.07.007
Chosa, T., Omine, M., & Itani, K. (2007). Dynamic performance of global positioning system velocity sensor for extremely accurate positioning. Biosystems Engineering, 97(1), 3–9. https://doi.org/10.1016/j.biosystemseng.2007.01.010
DOI: https://doi.org/10.1016/j.biosystemseng.2007.01.010
Freeland, R., Allred, B., Eash, N., Martinez, L., & Wishart, D. (2019). Agricultural drainage tile surveying using an unmanned aircraft vehicle paired with Real-Time Kinematic positioning—A case study. Computers and Electronics in Agriculture, 165, 104946. https://doi.org/10.1016/j.compag.2019.104946
DOI: https://doi.org/10.1016/j.compag.2019.104946
Guevara, J., Cheein, F., A., A., Gené-Mola, J., Rosell-Polo, J. R., & Gregorio, E. (2020). Analyzing and overcoming the effects of GNSS error on LiDAR based orchard parameters estimation. Computers and Electronics in Agriculture, 170, 105255. https://doi.org/10.1016/j.compag.2020.105255
DOI: https://doi.org/10.1016/j.compag.2020.105255
Guo, J., Li, X., Li, Z., Hu, L., Yang, G., Zhao, C., Fairbairn, D., Watson, D., & Ge, M. (2018). Multi-GNSS precise point positioning for precision agriculture. Precision Agriculture, 19(5), 895–911. https://doi.org/10.1007/s11119-018-9563-8
DOI: https://doi.org/10.1007/s11119-018-9563-8
Han, J. H., Park, C. H., Park, Y. J., & Kwon, J. H. (2019). Preliminary results of the development of a single-frequency GNSS RTK-based autonomous driving system for a speed sprayer. Journal of Sensors, 2019, 9. https://doi.org/10.1155/2019/4687819
DOI: https://doi.org/10.1155/2019/4687819
Hossein, M. (2013). A Technical Review on Navigation Systems of Agricultural Autonomous Off-road Vehicles. Journal of Terramechanics, 50(3), 211–232. https://doi.org/10.1016/j.jterra.2013.03.004
DOI: https://doi.org/10.1016/j.jterra.2013.03.004
Iida, M., Uchida, R., Zhu, H., Suguri, M., Kurita, H., & Masuda, R. (2013). Path-Following Control of a Head-Feeding Combine Robot. Engineering in Agriculture, Environment and Food, 6(2), 61–67. https://doi.org/10.1016/S1881-8366(13)80028-6
DOI: https://doi.org/10.1016/S1881-8366(13)80028-6
Japan Ministry of Agriculture. (2020). Forestry and fisheries. A new policy package to accelerate smart agriculture. https://www.maff.go.jp/j/press/kanbo/kihyo03/attach/pdf/201001-1.pdf. Retrieved June 24, 2021
Japan Ministry of Agriculture. (2021). Summary of findings. Forestry and fisheries, 2020 Census of Agriculture and Forestry, Government Statistical Codes: No.00500209,1-10.
Kabir, M., S., N., Song, M., Sung, N., Chung, S., Kim, Y., Noguchi, N., & Hong, S. (2016). Performance comparison of single and multi-GNSS receivers under agricultural fields in Korea. Engineering in Agriculture, Environment and Food, 9(1), 27–35. https://doi.org/10.1016/j.eaef.2015.09.002
DOI: https://doi.org/10.1016/j.eaef.2015.09.002
Kaizu, Y., Tsutsumi, T., Igarashi, S., & Imou, K. (2018). Development of autonomous driving control system for a robot mower using a low-cost single-frequency GNSS and a low-cost IMU. Journal of the Japanese Society of Agricultural Machinery and Food Engineering, 80(5), 271–279. https://www.jstage.jst.go.jp/article/jsamfe/80/5/80_271
Kawase, K. (2011). A More Concise Method of Calculation for the Coordinate Conversion between Geographic and Plane Rectangular Coordinates on the Gauss-Kruger Projection. Journal of the Geospatial Information Authority of Japan, 109–124. https://www.jstage.jst.go.jp/article/jsamfe/80/5/80_271
Kayacan, E., Kayacan, E., Ramon, H., & Saeys, W. (2014). Nonlinear modeling and identification of an autonomous tractor–trailer system. Computers and Electronics in Agriculture, 106, 1–10. https://doi.org/10.1016/j.compag.2014.05.002
DOI: https://doi.org/10.1016/j.compag.2014.05.002
Keicher, R., & Seufert, H. (2000). Automatic guidance for agricultural vehicles in Europe. Computers and Electronics in Agriculture, 25(1-2), 169–194. https://doi.org/10.1016/S0168-1699(99)00062-9
DOI: https://doi.org/10.1016/S0168-1699(99)00062-9
Kise, M., Noguchi, N., Ishii, K., & Terao, H. (2002). Field Mobile Robot Navigated by RTK-GPS and FOG (Part 3). Journal of the Japanese Society of Agricultural Machinery, 64(2), 102–110. https://doi.org/10.11357/jsam1937.64.2_102
Li, M., Imou, K., Wakabayashi, K., & Ykoyama, S. (2009). Review of research on agricultural vehicle autonomous guidance. International Journal of Agricultural and Biological Engineering, 2(3), 1-16. DOI: 10.3965/j.issn.1934-6344.2009.03.001-016 ; http://ijabe.org/index.php/ijabe/article/view/160
Madgwick, O.H.S., (2010). An efficient orientation filter for inertial and inertial/magnetic sensor arrays, Report x-io and University of Bristol (UK), 25, 113-118. https://forums.parallax.com/uploads/attachments/41167/106661.pdf
Matsuo, Y., Yukumoto, O., Yamamoto, S., Noguchi, N., & Hara, Y. (2009). Improvement of Adaptability and Reliability of Tilling Robot (Part 3). Journal of the Japanese Society of Agricultural Machinery, 71(3), 85–93. https://doi.org/10.11357/jsam.71.3_85
Miyamoto, J., Naomoto, T., Kubota, Y., Yoshida, K., & Ishimi, K. (2017). Rice Transplanter with Straight Keeping System. The Proceedings of Conference of Kansai Branch 2017.92,301. https://doi.org/10.1299/jsmekansai.2017.92.301
DOI: https://doi.org/10.1299/jsmekansai.2017.92.301
Nagasaka, Y., Taniwaki, K., Otani, R., Shigeta, K., & Sasaki, Y. (2000). The Development of Autonomous Rice Transplanter (Part 1). Journal of the Japanese Society of Agricultural Machinery, 61(6), 179–186. https://doi.org/10.11357/jsam1937.61.6_179
National Agriculture and Food Research Organization (2019). The number of deaths per 100,000 workers over 10 years. http://www.naro.affrc.go.jp/org/brain/anzenweb/shibou/pdf/20210216press-ref.pdf. Retrieved June 24, 2021.
Nagano Prefecture. (2020). Overview of the governor’s special area for direct agricultural payment scheme in mountainous areas. https://www.pref.nagano.lg.jp/noson/nosonshinko/documents/siryou2tokuningaiyou.pdf Retrieved June 24, 2021
Nørremark, M., Griepentrog, H. W., Nielsen, J., & Søgaard, H. T. (2008). The development and assessment of the accuracy of an autonomous GPS-based system for intra-row mechanical weed control in row crops. Biosystems Engineering, 101(4), 396–410. https://doi.org/10.1016/j.biosystemseng.2008.09.007
DOI: https://doi.org/10.1016/j.biosystemseng.2008.09.007
Ogura, Y. (2017). John Deere's Auto Trac Technology for Agriculture Vehicle. Journal of the Japanese Society of Agricultural Machinery and Food Engineers, 71(3), 85–93. https://doi.org/10.11357/jsamfe.79.6_457
Pérez-Ruiz, M., Carballido, J., Agüera, J., & Gil, J. A. (2011). Assessing GNSS correction signals for assisted guidance systems in agricultural vehicles. Precision Agriculture, 12(5), 639–652. https://doi.org/10.1007/s11119-010-9211-4
DOI: https://doi.org/10.1007/s11119-010-9211-4
Pérez-Ruiz, M., Martínez-Guanter, J., & Upadhyaya, K. S. (2021). Chapter 15 - High-precision GNSS for agricultural operations. GPS and GNSS Technology in Geosciences, 299–335. https://doi.org/10.1016/B978-0-12-818617-6.00017-2
DOI: https://doi.org/10.1016/B978-0-12-818617-6.00017-2
Pini, M., Marucco, G., Falco, G., Nicola, M., & Wilde, W. D. (2020). Experimental Testbed and Methodology for the Assessment of RTK GNSS Receivers Used in Precision Agriculture. IEEE Access, 8, 14690–14703. https://doi.org/10.1109/ACCESS.2020.2965741
DOI: https://doi.org/10.1109/ACCESS.2020.2965741
Rovira-Más, F., Chatterjee, I., & Sáiz-Rubio, V. (2015). The role of GNSS in the navigation strategies of cost-effective agricultural robots. Computers and Electronics in Agriculture, 112, 172–183. https://doi.org/10.1016/j.compag.2014.12.017
DOI: https://doi.org/10.1016/j.compag.2014.12.017
Santos, A. F., Silva, R. P., Zerbato, C., Menezes, P. C., Kazama, E. H., Paixão, C. S. S., & Voltarelli, M. A. (2019). Use of real-time extend GNSS for planting and inverting peanuts. Precision Agriculture, 20(4), 840–856. https://doi.org/10.1007/s11119-018-9616-z
DOI: https://doi.org/10.1007/s11119-018-9616-z
Søgaard, H., T., & Lund, I. (2000). Application Accuracy of a Machine Vision-controlled Robotic Micro-dosing System. Biosystems Engineering, 96(3), 315–322. https://doi.org/10.1016/j.biosystemseng.2006.11.009
DOI: https://doi.org/10.1016/j.biosystemseng.2006.11.009
Weise, G., Nagasaka, Y., & Taniwaki, K. (2000). Research Note (PM—Power and Machinery): An Investigation of the Turning Behaviour of an Autonomous Rice Transplanter. Journal of Agricultural Engineering Research, 77(2), 233–237. https://doi.org/10.1006/jaer.2000.0553
DOI: https://doi.org/10.1006/jaer.2000.0553
Zhang, Z., Noguchi, N., & Ishii, K. (2015). Development of a Robot Combine Harvester. Journal of the Japanese Society of Agricultural Machinery and Food Engineers, 77(1), 45–50. https://doi.org/10.11357/jsamfe.77.1_45
How to Cite
Hiraoka, R., Aoyagi, Y. and Kobayashi, K. (2023) “Automatic travelling of agricultural support robot for a fruit farm. Verification of effectiveness of real-time kinematic-global navigation satellite system and developed a simulator for specification design”, Journal of Agricultural Engineering, 54(1). doi: 10.4081/jae.2023.1355.
Copyright (c) 2023 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
