Development and evaluation of a general-purpose electric off-road robot based on agricultural navigation
Keywords:
electric off-road robot, automatic control, automatic steering, speed control, autonomous navigation system, field testAbstract
The aim of this study was to develop a general-purpose electric off-road robot vehicle by using automatic control technologies. The vehicle prototype used in this study was a commercially-purchased electricity utility vehicle that was designed originally for manual operations. A manipulating unit, an automatic steering system and a speed control system were developed and integrated into a CAN-bus network for operating on functions (forward, reverse, park or stop), realizing desired steering angles and maintaining a constant speed, respectively, in the mode of automation. An autonomous navigation system based on RTK-GPS and IMU was used to evaluate the performance of the newly developed off-road robot. Field tests showed that the maximum error in speed control was 0.29 m/s and 0.22 m/s for speed tests and autonomous runs, respectively. The lateral offset was less than 10 cm in terms of straight paths, indicating that the automatic steering control system was of good performance. Keywords: electric off-road robot, automatic control, automatic steering, speed control, autonomous navigation system, field test DOI: 10.3965/j.ijabe.20140705.002 Citation: Yin X, Noguchi 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.References
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[2] Inoue K, Nii K, Zhang Y, Atanasov A. Tractor guidance system for field work using GPS and GYRO. In: Proceedings of International Scientific Conference “Energy Efficiency & Agricultural Engineering”, 2009, Rousse, Bulgaria: 280–295.
[3] Backman J, Oksanen T, Visala A. Navigation system for agricultural machines: nonlinear model predictive path tracking. Computers and Electronics in Agriculture, 2012; 82: 32–43.
[4] Rovira-Más F. Global-referenced navigation grids for off-road vehicles and environments. Robotics and Autonomous Systems, 2012; 60(2): 278–287.
[5] Noguchi N, Will J, Reid J, Zhang Q. Development of a master-slave robot system for farm operations. Computers and Electronics in Agriculture, 2004; 44: 1–19.
[6] Bakker T, van Asselt K, Bontsema J, Müller J, van Straten G. Autonomous navigation using a robot platform in a sugar beet field. Biosystems Engineering, 2011; 109(4): 357–368.
[7] Tellaeche A, Pajares G, Burgos-Artizzu X P, Ribeiro A. A computer vision approach for weeds identification through Support Vector Machines. Applied Soft Computing, 2011; 11(1): 908–915.
[8] Xue J L, Zhang L, Grift T E. Variable field-of-view machine vision based row guidance of an agricultural robot. Computers and Electronics in Agriculture, 2012; 84: 85–91.
[9] Harper N, McKerrow P. Recognising plants with ultrasonic sensing for mobile robot navigation. Robotics and Autonomous Systems, 2001; 34(2–3): 71–82.
[10] Wang Q, Zhang Q, Rovira-Más F, Tian L. Stereovision- based lateral offset measurement for vehicle navigation in cultivated stubble fields. Biosystems Engineering, 2011; 109(4): 258–265.
[11] Kise M, Zhang Q, Rovira-Más F. A stereovision-based crop row detection method for tractor-automated guidance. Biosystems Engineering, 2005; 90(4): 357–367.
[12] 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.
[13] Yang L, Noguchi N. Human detection for a robot tractor using omni-directional stereo vision. Computers and Electronics in Agriculture, 2012; 89: 116–125.
[14] 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.
[15] Choi J, Yin X, Yang L, Noguchi N. Development of a laser scanner-based navigation system for a combine harvester. Engineering in Agriculture. Environment and Food, 2014; 7(1): 7–13.
[16] Hiremath S A, van der Heijden G W A M, van Evertb F K, Steinc A, ter Braaka C J F. Laser range finder model for autonomous navigation of a robot in a maize field using a particle filter. Computers and Electronics in Agriculture,
2014; 100: 41–50.
[17] Weiss U, Biber P. Plant detection and mapping for agricultural robots using a 3D LIDAR sensor. Robotics and Autonomous Systems, 2011; 59(5): 265–273.
[18] Debain C, Chateau T, Berducat M, Martinet P, Bonton P. A guidance-assistance system for agricultural vehicles. Computers and Electronics in Agriculture, 2000; 25: 29–51.
[19] Murakami N, Ito A, Will J D, Steffen M, Inoue K, Kita K, et al. Development of a teleoperation system for agricultural vehicles. Computers and Electronics in Agriculture, 2008; 63: 81–88.
[20] Bashiri B, Mann D D. Automation and the situation awareness of drivers in agricultural semi-autonomous
vehicles. Biosystems Engineering, 2014; 124: 8–15.
[21] Zhang Z, Luo X, Li J. Automatic steering control system of wheeled model farming machinery. Transactions of the CSAE, 2005; 21(11): 77–80. (in Chinese with English abstract)
[22] 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 with English abstract)
[23] Backman J, Oksanen T, Visala A. Applicability of the ISO 11783 network in a distributed combined guidance system for agricultural machines. Biosystems Engineering, 2013; 114(3): 306–317.
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Published
2014-10-30
How to Cite
Xiang, Y., & Noguchi, N. (2014). Development and evaluation of a general-purpose electric off-road robot based on agricultural navigation. International Journal of Agricultural and Biological Engineering, 7(5), 14–21. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/1328
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Power and Machinery Systems
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