International Journal of Agricultural Engineering

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Potential Aspects of Robotics in Indian Agriculture:Scope and Future


Affiliations
1 Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology, C.C.S. Haryana Agricultural University, Hisar (Haryana), India
     

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Robotics can play a very important role in Indian agriculture as far as the constantly decreasing size of farming fields is concerned. In comparison to foreign countries where the size of farm is large and heavy machinery can be used advantageously, this is not the case with Indian farms. In the process streamlining limited economic resources at farmer, robotics can reduce the burden by cutting cost on purchase in terms of quantity. Robotics uses small sized equipments to do the same operation which is very suitable for small sized farms. Precise use of costly pesticide and fertilizer can also be done by the automated robots. These brained machines can effectively perform repetitive agricultural operations with no or little error. The robots can also alleviate problems of traditional farming like soil compaction, use of renewable energy resources, drudgery etc. Many researchers have developed different agricultural robots in India and foreign countries. This paper deals with different robotic systems used in various agricultural operations in India as well as other countries. These are classified into several task groups such as planting, weeding, pest control, harvesting or picking, etc.

Keywords

Robotics, Agriculture, Drones, Autonomous Vehicles, Precision Farming.
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  • Astrand, B. and Baerveldt, A.J. (2004). Plant recognition and localization using context information, 2004. In: Proc. of the IEEE Conf. Mechatronics and Robotics 2004- special session. Autonomous Machines in Agriculture, Aachen, Germany.

  • Bakker, T., Asselt, K., Bontsema, J., Müller and Joachim Van Straten, G. (2005). An autonomous weeding robot for organic farming. Conference: Field and Service Robotics, Results of the 5th International Conference, FSR 2005, July 2931, 2005, Port Douglas, QLD, Australia, 25 : 579-590.

  • Bak, T. and Jakobsen, H. (2004). Agricultural robotic platform with four wheelsteering for weed detection. Biosystems Engg., 87(2) : 125-136 .

  • Balendonck, J., Hemming, J., Van, T. B., Pardossi, A., Incrocci, L. and Marzialetti, P. (2008). Sensors and wireless sensor networks for irrigation management under deficit conditions (FLOW-AID). International Conference on Agricultural Engineering (AgEng 2008). Conf. Proc. pp.19.

  • Blackmore, B.S., Fountas, S., Tang, L. and Have, H. (2004). Systems requirements for a small autonomous tractor. Agricultural Engineering International : The CIGR e-journal. PM 04.

  • Blasco, J., Aleixos, N., Roger, J. M., Rabatel, G. and Molt, E. (2002). Robotic weed control using machine vision. Biosyst. Engg., 83 : 149-157.

  • Benghanem, M. (2010). A low cost wireless data acquisition system for weather station monitoring. Renewable Energy, 35 (4) : 862-872.

  • Coates, R. W., Delwiche, M. J. and Brown, P. H. (2006).Control of individual micro-sprinklers and fault detection strategies. Precision Agriculture, 7 : 85-99.

  • Griepentrog, H. W., Ruckelshausen, A., Jorgensen, R.N. and Lund, I. (2010). Autonomous systems for plant protection in Precision Crop Protection – Challenge & Use of Heterogeneity, pp. 323-334.

  • Hemsworth, Michael (2017). The ‘AGRowBot’ Keeps an Eye on Crops on Small and Medium-Sized Farms. https:// www.trendhunter.com/trends/agrowbot.

  • Henten, E., Hemming, J. and Tuijl, B. (2002).An Autonomous Robot for Harvesting Cucumbers in Greenhouses. Autonomous Robots, 13 (3) : 241-258.

  • Hernandez, J. D., Barrientos, J., Cerro, J. D., Barrientos, A. and Sanz, D. (2013). Moisture measurement in crops using spherical robots. Industrial Robot: An Internat. J., 40(1) : 66.

  • Hussain, R., Sahgal, J. L. and Anshulgangwar, M. R. (2013). Control of irrigation automatically by using wireless sensor network. Internat. J. Soft Computing & Engg., 3(1) : 324-328.

  • Joshi, P. P. and Kanade, S. S. (2017). Wireless sensors and agriculture parameter monitoring: Experimental investigation. J. Electronics &Communic. Engg. Res., 3(8) : 6-13.

  • Kang, D. H., Hyeon, K., Dong, E. L., Gong, I, K., You, H. L., Hye, J. M. and Young, B. (2012). Development of a vegetable transplanting robot. J. Biosystems Engg., 37(3): 201-208.

  • Kayacan, E., Kayacan, E., Ramon, H. and Saeys, W. (2015). Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor. Computers & Electronics in Agriculture, 115 : 78–87. doi:10.1016/j.compag. 2015.05.012.

  • Keshtgary, M. and Deljoo, A. (2012). An efficient wireless sensor network for precision agriculture. Canadian J. Multimedia & Wireless Networks, 3(1):1-5.

  • Khattab, Y., Hassan, K. I., Shawkey, M. E., Abou El-Magd, A. M. and Sultan, W.M. (2018).Comparative study between laser beam transmitter, canopy temperature and soil moisture content under automate drip irrigation for cucumber in greenhouse. Agric Eng Int: CIGR J., 20 (4) : 26-31.

  • Khot, L., Tang, L., Blackmore, S. and Norremark, M. (2005). Posture estimation for autonomous weeding robots navigation in nursery tree plantations. In: Proceedings of the ASAE Annual Meeting; Paper number 053092.

  • Kim, Y., Evans, R.G. and Iversen, W. M. (2008). Remote sensing and control of an irrigation systems using a distributed wireless sensors network. IEEE Trans. Instrum. Meas., 57(7) : 1379-1387.

  • Kondo, N., Nishitsuji, Y., Ling, P. P. and Ting, K.C. (1996). Visual feedback guided robotic cherry tomato harvesting. Agric. & Biological Engg., 39(6) : 2331-2338.

  • Kondo, N., Monta, M. and Noguchi, N. (2006). Agri-robots (II) - mechanisms and practice, Corona Publishing Co., Ltd., Tokyo: 1-223pp.

  • Lamm, R. D., Slaughter, D.C. and Giles, D.K. (2002).Precision weed control system for cotton. Trans. ASAE, 45 (1) : 231-238.

  • Leemans, V. and Destain, M. F. (2007). A computer-vision based precision seed drill guidance assistance. Computers & Electronics in Agriculture, 59 (1-2) : 1-12.

  • Lee, W.S., Slaughter, D.C. and Giles, D.K. (1999). Robotic weed control system for tomatoes. Precision Agriculture, 1 (1) : 95-113.

  • Lopez, R. J. A., Sotoa, F., Suardiaza, F., Sancheza, P., Iborraa, A. and Verab, J.A. (2009). Wireless sensor networks for precision horticulture in Southern Spain. Computer Electronic Agriculture, 68 : 25-35.

  • Mahendheran, Arunprasanna, Manickavasagam, Justin, L. and Parthasarathi (2017).Multifunctional robotic vehicle for agriculture application. African J. Basic & Appl. Sci., 9 (1) : 16.

  • Maruyama, A. and Naruse, K. (2014).Development of small weeding robots for rice fields. 2014 IEEE/SICE International Symposium on System Integration.

  • Ming, L., Kenji, I., Katsuhiro, W. and Shinya, Y. (2009). Review of research on agricultural vehicle autonomous guidance. Internat. J. Agric. & Biological Engg., 2 (3) : 1-16.

  • Mizuno, A., Tenma, T. and Yamano, N. (1990).Destruction of weeds by pulsed high voltage discharges. Conference Record of the IEEE Industry Applications Society Annual Meeting, 1 : 720 – 727.

  • Mulla, D. J. (2013). Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engg., 114 (4) : 358-371.

  • Nagasaka, Y., Umeda, N., Kanetai, Y., Taniwaki, K. and Sasaki, Y. (2004). Autonomous guidance for rice transplanting using global positioning and gyroscopes. Computers &Electronics in Agriculture, 43 : 223-234.

  • Naik, D. A. and Thakur, H. M. (2017). Design and analysis of an automated seeder for small scale sowing applications for tray plantation method. Internat. J. Engg. Res. &Technol., 10 (1) : 716-723.

  • Ngaira, J. K. W. (2007). Impact of climate change on agriculture in Africa by 2030. Sci. Res. Essays, 2 (7) : 238-243.

  • Perez-Ruiz, M., Slaughter, D. C., Gliever, C. J. and Upadhyaya, S. K. (2012). Automatic GPS-based intra-row weed knife control system for transplanted row crops. Computers & Electronics in Agriculture, 80 : 41-49.

  • Pilli, S.K., Nallathambi, Bharathiraja, George, S. J. and Diwanji, V. (2015). eAGROBOT- A robot for early crop disease detection using image processing. 2015-2nd International Conference on Electronics and Communication Systems (ICECS), Coimbatore, 2015, pp. 1684-1689.

  • Rafi, R. H., Das, S., Ahmed, N., Hossain, I. and Reza, S. M. T. (2016). Design and implementation of a line following robot for irrigation based application. 2016-19th International Conference on Computer and Information Technology (ICCIT).

  • Santos, F. B. N.Dos, Sobreira, H.M.P., Campos, D.F.B., Santos, R.M.P.M. Dos, Moreira, A.P. G. M. and Contente, O.M.S. (2015). Towards a reliable monitoring robot for mountain vineyards. 2015 IEEE International Conference on Autonomous Robot Systems and Competitions.

  • Tang, X., Zhang, T., Liu, L., Xiao, D. and Chen, Y. (2008).A new robot system for harvesting cucumber. ASABE Annual International Meeting Sponsored by ASABE Grand Sierra Resort and Casino Reno, Nevada June 21- June 24, 2009.

  • Tanigaki, K., Fujiura, T., Akase, A. and Imagawa, J. (2008). Cherry-harvesting robot. Computers & Electronics in Agriculture, 63 : 65-72.

  • Torii, T. (2000). Research in autonomous agriculture vehicles in Japan. Computers & Electronics in Agriculture, 25(1-2): 133-153.

  • Valente, J., Sanz, D., Barrientos, A., Cerro, J., Ribeiro, A. and Rossi, C. (2011). An air-ground wireless sensor network for crop monitoring. Sensors, 11(6) : 6088-6108.

  • Zhang, Z. (2004). Investigation of wireless sensor networks for precision agriculture. ASAE Annual International Meeting. p. 041154.

  • Zhao, D. A., Lv, J., Ji, W., Zhang, Y. and Chen, Y. (2011). Design and control of an apple harvesting robot. Biosystems Engineering, 110 (2) : 112-122.

  • WEBLOGRAPHY

  • Anonymous (2018). Case study: AgBot II. Retrived from URL: https://www.qut.edu.au/research/partner-with-us/case-study-agbot-ii.

  • Holland, Will (2018). Terra Sentia: the automated crop monitoring robot. https://blog.plantwise.org/2018/07/17/terrasentia-the-automated-crop-monitoring-robot.


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  • Potential Aspects of Robotics in Indian Agriculture:Scope and Future

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Authors

Narender
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology, C.C.S. Haryana Agricultural University, Hisar (Haryana), India
Vinod Kumar
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology, C.C.S. Haryana Agricultural University, Hisar (Haryana), India
Vijaya Rani
Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology, C.C.S. Haryana Agricultural University, Hisar (Haryana), India

Abstract


Robotics can play a very important role in Indian agriculture as far as the constantly decreasing size of farming fields is concerned. In comparison to foreign countries where the size of farm is large and heavy machinery can be used advantageously, this is not the case with Indian farms. In the process streamlining limited economic resources at farmer, robotics can reduce the burden by cutting cost on purchase in terms of quantity. Robotics uses small sized equipments to do the same operation which is very suitable for small sized farms. Precise use of costly pesticide and fertilizer can also be done by the automated robots. These brained machines can effectively perform repetitive agricultural operations with no or little error. The robots can also alleviate problems of traditional farming like soil compaction, use of renewable energy resources, drudgery etc. Many researchers have developed different agricultural robots in India and foreign countries. This paper deals with different robotic systems used in various agricultural operations in India as well as other countries. These are classified into several task groups such as planting, weeding, pest control, harvesting or picking, etc.

Keywords


Robotics, Agriculture, Drones, Autonomous Vehicles, Precision Farming.

References