Development of autonomous navigation controller for agricultural vehicles
Keywords:
autonomous navigation, navigation controller, agricultural vehicles, straight-line tracking, straight path, headland turningAbstract
Agricultural vehicles are adopted to undertake farming tasks by traversing along crop rows in the field. Working quality depends significantly on the driving skills of the operator. Automatic guidance has been introduced into agriculture to achieve high-accuracy path tracking during the last decades, which contributes considerably to straight-line navigation. The objective of this research was to develop an autonomous navigation controller that allowed movement autonomy for various agricultural vehicles. Three wheel-type vehicles were used as the test platform featuring automatic steering, hydrostatic transmission and speed control, which included a rice transplanter, a high-clearance sprayer and a tractor. A dual-antenna RTK-GNSS receiver was attached to the vehicles to provide spatial information on both positioning and heading by using the RTX service from Trimble. A path planning method was proposed to create a straight-line reference path by giving two points, and the target path was determined according to the vehicle initial status and working assignment. Headland turning was comprehensively taken into account by listing different turn patterns in order to realize autonomous navigation at the headland. The navigation controller hardware was fabricated for program execution, data processing and information communication with peripherals. A human-machine interface was designed for the operator to complete basic setting, path planning and navigation control by providing controls. Field experiments were conducted to evaluate the performance and versatility of the newly developed autonomous navigation controller in guiding agricultural vehicles to follow straight paths and turn at the headland. Results showed that an appropriate turn pattern was automatically executed when finishing straight-line navigation. The lateral error in straight-line tracking was no more than 6 cm, 6 cm and 5 cm for the rice transplanter, the high-clearance sprayer and the tractor, respectively. And the maximum lateral RMS error was 3.10 cm, 4.75 cm, 2.21 cm in terms of straight-line tracking, which indicated that the newly developed autonomous navigation controller was versatile and of high robustness in guiding various agricultural vehicles. Keywords: autonomous navigation, navigation controller, agricultural vehicles, straight-line tracking, straight path, headland turning DOI: 10.25165/j.ijabe.20201304.5470 Citation: Yin X, Wang Y X, Chen Y L, Jin C Q, Du J. Development of autonomous navigation controller for agricultural vehicles. Int J Agric & Biol Eng, 2020; 13(4): 70–76.References
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[2] Tröster M F, Pahl H, Sauer J. Effects of application costs on fertilizer application strategy. Computers and Electronics in Agriculture, 2019; 167(2019): 105033. doi: 10.1016/j.compag.2019.105033.
[3] Wang Y, Zhou J, Ji C, An Q. Design of agricultural wheeled mobile robot based on autonomous navigation and omnidirectional steering. Transactions of the CSAE, 2008; 24(7): 110–113. (in Chinese)
[4] Rahul K, Raheman H, Paradkar V. Design and development of a 5R 2DOF parallel robot arm for handling paper pot seedlings in a vegetable transplanter. Computers and Electronics in Agriculture, 2019; 166(2019): 105014. doi: 10.1016/j.compag.2019.105014.
[5] Mohanraj I, Ashokumar K, Naren J. Field monitoring and automation using IOT in agriculture domain. Procedia Computer Science, 2016; 93(2016): 931–939.
[6] Thanpattranon P, Ahamed T, Takigawa T. Navigation of autonomous tractor for orchards and plantations using a laser range finder: Automatic control of trailer position with tractor. Biosystems Engineering, 2016; 147(2016): 90–103.
[7] Muñoz-Salinas R, Aguirre E, García-Silvente M. People detection and tracking using stereo vision and color. Image and Vision Computing, 2007; 25(6): 995–1007.
[8] Zhuang, Hou C, Tang Y, He Y, Luo S. Computer vision-based localisation of picking points for automatic litchi harvesting applications towards natural scenarios. Biosystems Engineering, 2019; 187(2019): 1–20.
[9] Zhao T, Noguchi N, Yang L, Ishii K, Chen J. Development of uncut crop edge detection system based on laser rangefinder for combine harvesters. Int J Agric & Biol Eng, 2016; 9(2): 21–28.
[10] Yin X, Noguchi N, Choi J. Development of a target recognition and following system for a field robot. Computers and Electronics in Agriculture, 2013; 98: 17–24.
[11] Yang L, Noguchi N, Takai R. Development and application of a wheel-type robot tractor. Engineering in Agriculture, Environment and Food, 2016; 9(2): 131–140.
[12] Tu X, Gai J, Tang L. Robust navigation control of a 4WD/4WS agricultural robotic vehicle. Computers and Electronics in Agriculture, 2019; 164(2019): 104892. doi: 10.1016/j.compag.2019.104892.
[13] Jones M H, Bell J, Dredge D, Seabright M, Scarfe A, Duke M, et al. Design and testing of a heavy-duty platform for autonomous navigation in kiwifruit orchards. Biosystems Engineering, 2019; 187(2019): 129–146.
[14] Harper N, McKerrow P. Recognising plants with ultrasonic sensing for mobile robot navigation. Robotics and Autonomous Systems, 2001; 34(2–3): 71–82.
[15] Mogens M. Graf Plessen. Partial field coverage based on two path planning patterns. Biosystems Engineering, 2018; 171(2018): 16–29.
[16] Jensen M A F, Bochtis D, Sørensen C G, Blas M R, Lykkegaard K L. In-field and inter-field path planning for agricultural transport units. Computers & Industrial Engineering, 2012; 63(4): 1054–1061.
[17] Zhang Z, Noguchi N, Ishii K, Yang L. Optimization of steering control parameters based on a combine harvester's kinematic model. Engineering in Agriculture, Environment and Food, 2014; 7(2): 91–96.
[18] Yin X, Du J, Noguchi N, Yang T, Jin C. Development of autonomous navigation system for rice transplanter. Int J Agric & Biol Eng, 2018; 11(6): 89–94.
[19] Yao J, Teng G, Huo L, Yuan Y, Zhang F. Optimization of cooperative operation path for multiple combine harvesters without conflict. Transactions of the CSAE, 2019; 35(17): 12–18. (in Chinese)
[20] Wang H, Wang G, Luo X, Zhang Z, Gao Y, He J, Yue B. Path tracking control method of agricultural machine navigation based on aiming pursuit model. Transactions of the CSAE, 2019; 35(4): 11–19. (in Chinese)
[21] Yin X, Noboru N. Development and evaluation of a general-purpose electric off-road robot based on agricultural navigation. Int J Agric & Biol Eng, 2014; 7(5): 14–21.
[22] Wei S, Li S, Zhang M, Ji Y, Xiang M, Li M. Automatic navigation path search and turning control of agricultural machinery based on GNSS. Transactions of the CSAE, 2017; 33(Z1): 70–77. (in Chinese)
[23] Holpp M, Kroulik M, Kviz Z, Anken T, Sauter M, Hensel O. Large-scale field evaluation of driving performance and ergonomic effects of satellite-based guidance systems. Biosystems Engineering, 2013; 116(2013): 190 –197.
[24] Spekken M, Molin J P, Romanelli T L. Cost of boundary manoeuvres in sugarcane production. Biosystems Engineering, 2015; 129(2015): 112–126.
[25] Zhou K, Leck A J, Bochtis D D, Sørensen C G. Quantifying the benefits of alternative fieldwork patterns in a potato cultivation system. Computers and Electronics in Agriculture, 2015; 119 (2015): 228–240.
[26] Liu Z, Zhang Z, Luo X, Wang H, Huang P, Zhang J. Design of automatic navigation operation system for Lovol ZP9500 high clearance boom sprayer based on GNSS. Transactions of the CSAE, 2018; 34(1): 15–21. (in Chinese)
[27] Yang L, Wang Z, Luo J, Zhao Y, Li W, Bi B. Design and implementation of Xinjiang farmland navigation system based on android development. Transactions of the CSAM, 2019; 50(Supp): 57–61. (in Chinese)
[28] Li Y, Zhao Z, Huang P, Guan W, Wu X. Automatic navigation system of tractor based on DGPS and double closed-loop steering control. Transactions of the CSAM, 2017; 48(2): 11–19. (in Chinese)
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Published
2020-08-07
How to Cite
Yin, X., Wang, Y., Chen, Y., Jin, C., & Du, J. (2020). Development of autonomous navigation controller for agricultural vehicles. International Journal of Agricultural and Biological Engineering, 13(4), 70–76. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/5470
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Power and Machinery Systems
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