Machine Vision and Global Positioning System for Autonomous Robotic Navigation in Agriculture: A Review
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Published:
Mar 13, 2017
Keywords:
Machine Vision, GPS, navigation, Agriculture
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Abstract
Interest on robotic agriculture system has led to the development of agricultural robots that helps to improve the farming operation and increase the agriculture productivity. Much research has been conducted to increase the capability of the robot to assist agricultural operation, which leads to development of autonomous robot. This development provides a means of reducing agricultures dependency on operators, workers, also reducing the inaccuracy caused by human errors. There are two important development components for autonomous navigation. The first component is Machine vision for guiding through the crops and the second component is GPS technology to guide the robot through the agricultural fields.
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Volume 01 Nomor 01
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[4] Gan-Mor, Samuel, et al. œGuidance of Autonomous Vehicle for Greenhouse Transportation. ACTA Horticulture, no 443 (1997): 99104.
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[6] Gan-Mor, Samuel, et al. œDGPS Tractor Guidance : Implement Guidance Error as Affected by Field Conditions using Automatic. American Society of Agricultural Engineers Paper, no 021153 (2002).
[7] Subramanian, A., T. F. Burks, and A. A. Aroyyo. œDevelopment of Machine Vision and Laser Radar Based Autonomous Vehicle Guidance Systems for Citrus Grove Navigation. Computers and Electronics in Agriculture 53 (2006): 130-143.
[8] Paul, Andre. œDesign of An Autonomous Navigation System for A Mobile Robot. Master Thesis., University of McGill, Montreal, 2005.
[9] Zhang, N., M. Wang, and N. Wang. œPrecision Agriculture-A World Wide Overview. Computers and Electronics in Agriculture 36 (2002): 113-132.
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[11] Gan-Mor, Samuel, et al. œDGPS Tractor Guidance : Implement Guidance Error as Affected by Field Conditions using Automatic. American Society of Agricultural Engineers Paper, no 021153 (2002).
[12] Gan-Mor, Samuel; Bruce L. Upchurch and Rex L. Clark. œGPS Tractor Guidance : Implement Laterat Position Accuracy Inder RTK. Computer and Electronics in Agriculture, no 59 (2007): 31-38.
[13] M. OConnor et al, ˜Tractor drivers soon may say, œ Look, Ma! No hands! , Stanford Report 1997. [Online]. Available: http://news.stanford.edu/news/1997/september24/gsbtractor.html. [Accessed: 02- Jun- 2011].
[14] Yang, Linghe. œA Fruit Recognition Method for Automatic Harvesting. Master Thesis., University of Windsor, Canada, 2007.
[15] E. Segerblad, and Bjorn Delight ˜Machine Vision in Agricultural Robotics A short overview, IDT Workshop on Interesting Results in Computer Science and Engineering. [Online]. Available: http://www.idt.mdh.se/kurser/ct3340/ht11/MINICONFERENCE/FinalPapers/ircse11_submission_2.pdf. [Accessed: 10- Jun- 2011].
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[20] T. Junhua., H. Jiang, and W. Zhou. œDevelopment of Automoatic System for the Seedling Trasplanter Based on Machine Vision Technology College of Biosystems Engineering and Food Science. Zhenjiang University, (2010).
[21] Zhao, C. W. Huang, L. Chen, Z. Meng, Y. Wang, and F. Xu. œHarvest Area Measurement System Based on Ultrasonic Sensors and DGPS for Yield Map Correction. Precision Agric 11, (2010): 163-180.
[22] .Xue, J., L. Zhang, T.E. Grift. œVariable field-pf-view machine vision based row guidance of an agricultural robot.. Computer and Electronics in Agriculture, no. 84 (2012) 85-91.
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[24] Xue, J., L. Xu. œAutonomous agricultural robot and its row guidance. 2010 International conference on Measuring Technology and Mechatronics Automation, 1 (2010) 725-729.
[25] Hague, T., J. A. Marchant, and N. D. Tillett. œGround Based Sensing Systems for Autonomous Agriclutural Vehicles. Computers and Electronics in Agriculture 25 (2000): 11-28.
[26] Harrel, R. C., P. D. Adsit, R. D. Munilla and D. C. Slaughter. œRobotic Picking Citrus. Robotica 8, no 4 (1990): 269-278.
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[28] Kaizu, Y., and K. Imou. œA Dual-Spectral camera system for paddy rice seedling row detection. Computers and Electronics in Agriculture, 63 (2008). 49-56.
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[30] Hague, T., J. A. Marchant, and N. D. Tillett. œGround Based Sensing Systems for Autonomous Agriclutural Vehicles. Computers and Electronics in Agriculture 25 (2000):11-28.