Dual-Unloading Mode Autonomous Operation Strategy and Cotransporter System for Rice Harvester and Transporter

doi:10.1016/j.eng.2024.11.006

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Engineering ›› 2025, Vol. 48 ›› Issue (5) : 220-233. DOI: 10.1016/j.eng.2024.11.006

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Dual-Unloading Mode Autonomous Operation Strategy and Cotransporter System for Rice Harvester and Transporter

Fan Ding^a^,^c, Xiwen Luo^a^,^b^,^c, Zhigang Zhang^a^,^b^,^c, Lian Hu^a^,^b^,^c, Xinluo Wu^a^,^c, Kaiyuan Bao^a^,^c, Jiarui Zhang^a^,^c, Bingxuan Yuan^a^,^c, Wenyu Zhang^a^,^b^,^c

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Abstract

To achieve an unmanned rice farm, in this study, a cotransporter system was developed using a tracked rice harvester and transporter for autonomous harvesting, unloading, and transportation. Additionally, two unloading and transportation modes—harvester waiting for unloading (HWU) and transporter following for unloading (TFU)--were proposed, and a harvesting-unloading-transportation (HUT) strategy was defined. By breaking down the main stages of the collaborative operation, designing Module-state machines (MSMs), and constructing state-transition chains, a HUT collaborative operation logic framework suitable for the embedded navigation controller was designed using the concept and method of the finite-state machine (FSM). This method addresses the multiple-stage, nonsequential, and complex processes in HUT collaborative operations. Simulations and field-harvesting experiments were performed to evaluate the applicability of this proposed strategy and system. The experimental results showed that the HUT collaborative operation strategy effectively integrated path planning, path-tracking control, inter-vehicle communication, collaborative operation control, and implementation control. The cotransporter system completed the entire process of harvesting, unloading, and transportation. The field-harvesting experiment revealed that a harvest efficiency of 0.42 hm²∙h⁻¹ was achieved. This study can provide insight into collaborative harvesting and solutions for the harvesting process of unmanned farms.

Keywords

Agricultural machinery / Harvesting-unloading-transportation strategy / Cotransporter system / Unmanned farm / Finite-state machine (FSM)

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Fan Ding, Xiwen Luo, Zhigang Zhang, Lian Hu, Xinluo Wu, Kaiyuan Bao, Jiarui Zhang, Bingxuan Yuan, Wenyu Zhang. Dual-Unloading Mode Autonomous Operation Strategy and Cotransporter System for Rice Harvester and Transporter. Engineering, 2025, 48(5): 220‒233 https://doi.org/10.1016/j.eng.2024.11.006

References

[1]	D. Li, Z. Li. System analysis and development prospect of unmanned farming. Trans Chin Soc Agric Mach, 51 (7) ( 2020), pp. 1-12(Chinese).
[2]	X. Luo, J. Liao, L. Hu, Z. Zhou, Z. Zhang, Y. Zang, et al.. Research progress of intelligent agricultural machinery and practice of unmanned farm in China. J South China Agric Univ, 42 (6) ( 2021), pp. 8-17(Chinese).
[3]	Z. Zhang, X. Luo, Z. Zhao, P. Huang. Trajectory tracking control method based on kalman filter and pure pursuit model for agricultural vehicle. Trans Chin Soc Agric Mach, 40 (S1) ( 2009), pp. 6-12(Chinese).
[4]	H. Chou, F. Khorsandi, S. Vougioukas, F. Fathallah. Developing and evaluating an autonomous agricultural all-terrain vehicle for field experimental rollover simulations. Comput Electron Agric, 194 ( 2022), Article 106735
[5]	H. Sun, D. Slaughter, M. Ruiz, C. Gliever, S. Upadhyaya, R. Smith. Rtk gps mapping of transplanted row crops. Comput Electron Agric, 71 (1) ( 2010), pp. 32-37
[6]	Y. Ding, Z. Xia, J. Peng, Z. Hu. Design and experiment of the single-neuron PID navigation controller for a combine harvester. Trans Chin Soc Agric Eng, 36 (7) ( 2020), pp. 34-42(Chinese).
[7]	J. Xue, L. Zhang, T. Grift. Variable field-of-view machine vision based row guidance of an agricultural robot. Comput Electron Agric, 84 ( 2012), pp. 85-91
[8]	Y. Zhang, Y. Li, X. Liu, J. Tao, C. Liu, R. Li. Fuzzy adaptive control method for autonomous rice seeder. Trans Chin Soc Agric Mach, 49 (10) ( 2018), pp. 30-37(Chinese).
[9]	X. Niu, G. Gao, Z. Bao, H. Zhou. Path tracking of mobile robots for greenhouse spraying controlled by sliding mode variable structure. Trans Chin Soc Agric Eng, 29 (02) ( 2013), pp. 9-16(Chinese).
[10]	G. Xu, M. Chen, X. He, H. Pang, H. Miao, P. Cui, et al.. Path following control of tractor with an electro-hydraulic coupling steering system: layered multi-loop robust control architecture. Biosyst Eng, 209 ( 2021), pp. 282-299
[11]	J. He, L. Hu, P. Wang, Y. Liu, Z. Man, T. Tu, et al.. Path tracking control method and performance test based on agricultural machinery pose correction. Comput Electron Agric, 200 ( 2022), Article 107185
[12]	R. Chi, Z. Xiong, L. Jiang, Y. Ma, X. Huang, X. Zhu. Path tracking control algorithm of transplanter based on model prediction. Trans Chin Soc Agric Mach, 53 (11) ( 2022), pp. 22-30(Chinese).
[13]	X. Zhang, M. Geimer, P. Noack, L. Grandl. A semi-autonomous tractor in an intelligent master-slave vehicle system. Intell Serv Robot, 3 (4) ( 2010), pp. 263-269
[14]	S. Li, R. Cao, S. Wei, Y. Ji, M. Zhang, H. Li. Development of multivehicle cooperative navigation communication system based on TD-LTE. Trans Chin Soc Agric Mach, 48 (S1) ( 2017), pp. 45-51(Chinese).
[15]	C. Zhang, N. Noguchi, L. Yang. Leader-follower system using two robot tractors to improve work efficiency. Comput Electron Agric, 121 ( 2016), pp. 269-281
[16]	J. Chen, S. Fu, Z. Guan, F. Zhu, L. Zhu, H. Xia, et al.. Communication method for combine harvester group using Lora technology. Trans Chin Soc Agric Eng, 38 (16) ( 2022), pp. 81-89(Chinese).
[17]	J. Yao, G. Teng, L. Huo, Y. Yuan, F. Zhang. Optimization of cooperative operation path for multiple combine harvesters without conflict. Trans Chin Soc Agric Eng, 35 (17) ( 2019), pp. 12-18(Chinese).
[18]	Z. Zhai, X. Wang, L. Wang, Z. Zhu, Y. Du, E. Mao. Collaborative path planning for autonomous agricultural machinery of master slave cooperation. Trans Chin Soc Agric Mach, 52 (S1) ( 2021), pp. 542-547(Chinese).
[19]	F. Zhang, X. Luo, Z. Zhang, J. He, W. Zhang. Agricultural machinery scheduling optimization method based on improved multi-parents genetic algorithm. Trans Chin Soc Agric Eng, 37 (9) ( 2021), pp. 192-198(Chinese).
[20]	N. Wang, X. Yang, T. Wang, J. Xiao, M. Zhang, H. Wang, et al.. Collaborative path planning and task allocation for multiple agricultural machines. Comput Electron Agric, 213 ( 2023), Article 108218
[21]	N. Noguchi, J. Will, J. Reid, Q. Zhang. Development of a master-slave robot system for farm operations. Comput Electron Agric, 44 (1) ( 2004), pp. 1-19
[22]	X. Bai, Z. Wang, J. Hu, L. Gao, F. Xiong. Harvester group corporative navigation method based on leader-follower structure. Trans Chin Soc Agric Mach, 48 (7) ( 2017), pp. 14-21(Chinese).
[23]	S. Li, H. Xu, Y. Ji, R. Cao, M. Zhang, H. Li. Development of a following agricultural machinery automatic navigation system. Comput Electron Agric, 158 ( 2019), pp. 335-344
[24]	W. Zhang, Z. Zhang, X. Luo, J. He, L. Hu, B. Yue. Position-velocity coupling control method and experiments for longitudinal relative position of harvester and grain truck. Trans Chin Soc Agric Eng, 37 (9) ( 2021), pp. 1-11(Chinese).
[25]	F. Ding, W. Zhang, X. Luo, L. Hu, Z. Zhang, M. Wang, et al.. Gain self-adjusting single neuron pid control method and experiments for longitudinal relative position of harvester and transport vehicle. Comput Electron Agric, 213 ( 2023), Article 108215
[26]	H. Cho, G.D. Hachtel, E. Macii, B. Plessier, F. Somenzi. Algorithms for approximate fsm traversal based on state space decomposition. IEEE Trans Comput Aided Des Integrated Circ Syst, 15 (12) ( 1996), pp. 1465-1478
[27]	J. Leonard, J. How, S. Teller, M. Berger, S. Campbell, G. Fiore, et al.. A perception-driven autonomous urban vehicle. J Field Robot, 25 (10) ( 2008), pp. 727-774
[28]	A. Talebpour, H. Mahmassani, S. Hamdar. Modeling lane-changing behavior in a connected environment: a game theory approach. Transp Res Procedia, 7 ( 2015), pp. 420-440
[29]	L. Xiong, T. Jia, J. Chen, X. Xing, B. Li. Hazard identification method for safety of the intended functionality based on finite state machine. J Tongji Univ, 51 (4) ( 2023), pp. 616-622(Chinese).
[30]	L. Yang, X. Tang, S. Wu, L. Wen, W. Yang, C. Wu. Local path planning for autonomous agricultural machinery on farm road. Trans Chin Soc Agric Eng, 40 (01) ( 2024), pp. 27-36(Chinese).
[31]	K. Fue, W. Porter, E. Barnes, C. Li, G. Rains. Center-articulated hydrostatic cotton harvesting rover using visual-servoing control and a finite state machine. Electronics, 9 (8) ( 2020), p. 1226
[32]	J. He, X. Luo, Z. Zhang, P. Wang, J. He, B. Yue, et al.. Positioning correction method for rice transplanters based on the attitude of the implement. Comput Electron Agric, 176 ( 2020), Article 105598
[33]	H. Wang, G. Wang, X. Luo, Z. Zhang, Y. Gao, J. He, et al.. Path tracking control method of agricultural machine navigation based on aiming pursuit model. Trans Chin Soc Agric Eng, 35 (4) ( 2019), pp. 11-19(Chinese).
[34]	F. Ding, W. Zhang, X. Luo, Z. Zhang, M. Wang, H. Li, et al.. Design and experiment for inter-vehicle communication based on dead-reckoning and delay compensation in a cooperative harvester and transport system. Agriculture, 12 (12) ( 2022), p. 2052
[35]	W. Zhang, L. Hu, F. Ding, X. Luo, Z. Zhang, L. Hu, et al.. Parking precise alignment control and cotransporter system for rice harvester and transporter. Comput Electron Agric, 215 ( 2023), Article 108443
[36]	Y. Tian, S. Bhattacharya. Smart autonomous grain carts for harvesting-on-demand, IEEE, Vancouver, BC, Canada. Piscataway ( 2017), pp. 5168-5173
[37]	P. He, J. Li. The two-echelon multi-trip vehicle routing problem with dynamic satellites for crop harvesting and transportation. Appl Soft Comput, 77 ( 2019), pp. 387-398
[38]	W. Zhang, Z. Zhang, F. Zhang, F. Ding, L. Hu, X. Luo. Cooperative autonomous operation strategy and experiment of the rice harvester together with a rice-transporting vehicle. Trans Chin Soc Agric Eng, 38 (15) ( 2022), pp. 1-9(Chinese).
[39]	S. Li, M. Zhang, N. Wang, R. Cao, Z. Zhang, Y. Ji, et al.. Intelligent scheduling method for multi-machine cooperative operation based on nsga-iii and improved ant colony algorithm. Comput Electron Agric, 204 ( 2023), Article 107532