Review of open-field vegetable automatic following transportation technology and equipment
Keywords:
vegetables, field transport, positioning technology, automatic following technology, path trackingAbstract
The vegetable industry is the largest sector within China’s planting industry. The integration of modern informationtechnologies such as big data and the Internet of Things (IoT) with agricultural equipment has facilitated the intelligentupgrading and transformation of the vegetable industry. This paper addresses the lack of automatic field transportationequipment for open-field vegetables. Around the main production scenarios of open-field vegetables, this paper summarizes theresearch status of field transportation equipment at home and abroad, and compares the characteristics of oil-powered andelectric transporters. The paper also points out that the automatic following technology of field transportation equipment is acrucial technology for achieving coordinated harvesting and transportation. It proposes that automatic following technology isprimarily realized through navigation and positioning technology and path tracking technology, and elaborates on theapplication research status of both. Based on this, the paper outlines the current application of field transporters in China,identifying issues such as poor integration of agricultural machinery and agronomy, poor adaptability of transport vehicles,poor navigation and positioning stability, insufficient environmental adaptability of path tracking algorithms, and immaturemulti-machine coordination technology for field transportation. The future development trends of standardized vegetableplanting, optimization of transportation equipment structure, precision and intelligence of automatic following technology,multi-machine collaborative operation, and emphasis on energy utilization and environmental protection are proposed. Finally,the paper summarizes the applicable scenarios of field transportation equipment, navigation and positioning modes, and pathtracking algorithms in conjunction with the content of the full text.
Keywords: vegetables, field transport, positioning technology, automatic following technology, path tracking
DOI: 10.25165/j.ijabe.20261904.9963
Citation: Zhang J F, Tang J C, Song Z Y, Liu J B, Ning X F, Cao G Q. Review of open-field vegetable automatic following transportation technology and equipment. Int J Agric & Biol Eng, 2026; 19(4): 1–15.
References
[1] An M, Cao S S, Sun W, Kong H X, Kong F T, Liu J F. Research on market operation trend of vegetable industry in China. Chinese Vegetables, 2024; 2: 6–13. (in Chinese)
[2] Chen W M, Hu L L, Yuan J N, Wang G P, Wang B, Wu W. Research status and prospect of automatic control technology of vegetable harvester in China. Journal of Intelligent Agricultural Mechanization, 2021; 2: 57–63. (in Chinese)
[3] Chen Y S, Liu X C, Han B H, Cui Z C, Yang Y T, Guan C S, et al. Development report of China vegetable production mechanization in 2020. Journal of Chinese Agricultural Mechanization, 2021; 42: 1–9. (in Chinese)
[4] Gao F, Sa J, Wang Z, Peng Q. Development and application of intelligent agricultural machinery—A review. 7th International Conference on Big Data Analytics (ICBDA), Guangzhou, China, March 04-06, 2022. DOI: 10.1109/ICBDA55095.2022.9760367
[5] Chen R, Xu P, Song P, Wang M, He J. China has faster pace than Japan in population aging in next 25 years. BioScience Trends, 2019; 13: 287–291.
[6] Shi Y J, Cheng X H, Xi X B, Shan X, Jin Y F, Zhang R H. Research progress on the path tracking control methods for agricultural machinery navigation. Transactions of the CSAE, 2023; 39(15): 1–14. (in Chinese)
[7] Wei W, Xiao M, Duan W, Wang H, Zhu Y, Zhai C, et al. Research progress on autonomous operation technology for agricultural equipment in large fields. Agriculture, 2024; 14: 1473.
[8] Wu C J, Tang X L, Xu X Y. System design, analysis, and control of an intelligent vehicle for transportation in greenhouse. Agriculture, 2023; 13: 1020.
[9] Hong Y, Xu J, Fang J C. Design and development of gearbox for crawler agricultural carrier. Internal Combustion Engine & Parts, 2023; 10: 6–8. (in Chinese)
[10] Chen M, Zhang Y L, Li S J, Meng L, Zhang W. Design and experiment of the walking transport vehicle with single crawler for mountain orchard. Journal of Huazhong Agricultural University, 2019; 38: 125–132. (in Chinese)
[11] Zhou H Y, Xu D, Hu T. Innovative design of orchard transport vehicle based on user demand. Packaging Engineering, 2022; 43: 306–312. (in Chinese)
[12] Xu L Y, Zhang J J, Yan X H, Zhao S X, Wu Y W, Liu M N. Review of research for agricultural equipment electrification technology. Transactions of the CSAM, 2023; 54: 1–12. (in Chinese)
[13] Liu W Q. Structural optimization design and stability research of caterpillar orchard working platform. Agricultural University of Hebei, Baoding, China, 2022. (in Chinese). DOI: 10.27109/d.cnki.ghbnu.2022.000733
[14] Han Z H, Zhu L C, Yuan Y W, Zhao B, Fang X, Wang D. Design and test of transport vehicle for hillside orchards based on center of gravity regulation. Transactions of the CSAM, 2022; 53(2): 430–442. (in Chinese)
[15] Yu J. Design and experimental research of selective harvesting autonomous following transportation platform for field cauliflower vegetables. Jiangsu University, Zhenjiang, China, 2023. (in Chinese). DOI: 10.27170/d.cnki.gjsuu.2023.001446
[16] Qu J, Zhang Z, Qin Z, Guo K, Li D. Applications of autonomous navigation technologies for unmanned agricultural tractors: A review. Machines, 2024; 12: 218.
[17] Xie B, Jin Y, Faheem M, Gao W, Liu J, Jiang H, et al. Research progress of autonomous navigation technology for multi-agricultural scenes. Computers and Electronics in Agriculture, 2023; 211: 107963.
[18] Xu H, Geng D, Fan Z, Wu D, Chen M. An automatic vehicle navigation system based on filters integrating inertial navigation and global positioning systems. Machines, 2024; 12: 663.
[19] Zhang Y Y, Zhang B, Shen C, Liu H L, Huang J C, Tian K P, et al. Review of the field environmental sensing methods based on multi-sensor information fusion technology. Int J Agric & Biol Eng, 2024; 17(2): 1–13.
[20] Yang X R, Fang K, Xie L, Lai J. Infrared obstacle avoidance trolley design based on microcontroller. Modern Industrial Economy and Informationization, 2023; 13: 253–255. (in Chinese)
[21] Essien J, Chimezie C. Ultrasonic sensor-based embedded system for vehicular collusion detection and alert. Journal of Computer and Communications, 2023; 11: 44–57.
[22] Krishnan P. Design of collision detection system for smart car using Li-Fi and ultrasonic sensor. IEEE Transactions on Vehicular Technology, 2018; 67: 11420–11426.
[23] Shen X P. Design of automatic planning system for obstacle avoidance route of intelligent mobile robot. Machine Building & Automation, 2023; 52: 28–31. (in Chinese)
[24] Song A W, Wang L, Liu Y M, Yuan W, Qiu T, Xiao X. Design of mobile robot positioning system based on incremental PID algorithm. Journal of Hunan University of Arts and Science (Natural Science Edition), 2024; 36: 19–26. (in Chinese)
[25] Qi K, Song Z B, Dai J S. Safe physical human-robot interaction: A quasi whole-body sensing method based on novel laser-ranging sensor ring pairs. Robotics and Computer-Integrated Manufacturing, 2022; 75: 102280.
[26] Zhao P, Lu X C, Wang J, Chen C, Wang W, Trigoni N, et al. Human tracking and identification through a millimeter wave radar. Ad Hoc Networks, 2021; 116: 102475.
[27] Ikram M Z, Ahmad A, Wang D. High-accuracy distance measurement using millimeter-wave radar. 2018 IEEE Radar Conference (RadarConf18), Oklahoma City, USA, 11 June 2018. DOI: 10.1109/RADAR.2018.8378750
[28] Wang P W, Liu C, Zhang J, Wang L, Zhang M F. DS-UKF-based positioning method for intelligent connected vehicles in urban intersection scenarios. IEEE Trans. Intell. Transp. Syst, 2024; 25: 6118–6132.
[29] Gao J Z, Kou Z W, Kong Z, Jing G, Ma J, Xu H. Design of location and mapping algorithm of pasture inspection robot based on LiDAR. Journal of Chinese Agricultural Mechanization, 2024; 45: 222–230. (in Chinese)
[30] Jin S, Meng X, Dardanelli G, Zhu Y. Multi-global navigation satellite system for earth observation: Recent developments and new progress. Remote Sensing, 2024; 16: 4800.
[31] Qi Y C. Research on differential GNSS with multiple antennas. Dalian University of Technology, Dalian, China, 2020. (in Chinese) DOI: 10.26991/d.cnki.gdllu.2020.000581
[32] Zhou X L, Guan J X, Yang Y M, Xue B H. Research on vehicle deviation detection system based on GPS-RTK. China Measurement & Test, 2020; 46: 83–87. (in Chinese)
[33] Morales J, Martínez J L, García-Cerezo A J. A redundant configuration of four low-cost GNSS-RTK receivers for reliable estimation of vehicular position and posture. Sensors, 2021; 21: 5853.
[34] Liao L X, Chen X H, Yang G Y. Research on intelligent paddy field grader based on RTK-GNSS. Journal of Agricultural Mechanization Research, 2024; 46: 131–135, 140. (in Chinese)
[35] Wei W C, Pan S G, Teng X L, Zhang M, Gao W, Jiang Y Y. Differential carrier phase kinematic post-processing method based on BDS multi-frequency observations. 14th China Satellite Navigation Conference, Jinan, China, May 2024. DOI: 10.26914/c.cnkihy.2024.000176
[36] Guo J, Li X, Li Z, Hu L, Yang G, Zhao C, et al. Multi-GNSS precise point positioning for precision agriculture. Precision Agriculture, 2018; 19: 895–911.
[37] Wang H. Study on indoor positioning technology based on inertial sensors. Yanshan University, Qinhuangdao, China, 2023. (in Chinese) DOI: 10.27440/d.cnki.gysdu.2023.002020
[38] Huang F R, Yi B H, Wang X, Liu Q, Wang W. Vehicle inertial navigation method based on deep learning and motion constraints. Journal of Chinese Inertial Technology, 2022; 30: 569–575. (in Chinese)
[39] Sun Y, Guan L, Chang Z, Li C, Gao Y. Design of a low-cost indoor navigation system for food delivery robot based on multi-sensor information fusion. Sensors, 2019; 19: 4980.
[40] Yan D, Song W, Wang X, Hu Z. Review of development status of indoor location technology in China. Journal of Navigation and Positioning, 2019; 7: 5–12. (in Chinese)
[41] Dong Y, Lu X, Peng F R, Zhang T. UWB indoor positioning calibration method based on TOA algorithm. Measurement & Control Technology, 2023; 42: 47–52. (in Chinese)
[42] Fang X B, Lin Y, Su Y A, Zhong L. UWB indoor positioning algorithm based on TOF and adaptive robust KF. Transducer and Microsystem Technologies, 2024; 43: 134–138. (in Chinese)
[43] Wu Y S, Fei T L. UWB vehicle tag tracking method in tunnels. Journal of Navigation and Positioning, 2024; 12: 181–189. (in Chinese)
[44] Tunç F A, Alp Y K, Ata L D. Location estimation by using multiple TDOA/AOA measurements. 2020 28th Signal Processing and Communications Applications Conference (SIU), Gaziantep, Turkey, October 5-7, 2020. DOI: 10.1109/SIU49456.2020.9302313
[45] Ji S Y, Wang Y S. Research on ranging method based on monocular vision and LiDAR. Ship Electronic Engineering, 2022; 42: 180–184. (in Chinese). DOI: 10. 3969/j. issn. 1672-9730. 2022. 02. 039
[46] Sun X, Jiang Y, Ji Y, Fu W, Yan S, Chen Q, et al. Distance measurement system based on binocular stereo vision. IOP Conference Series: Earth and Environmental Science, 2019; 252: 052051.
[47] Zheng W Q, Wang D. Research on indoor mobile robot obstacle avoidance based on ROS. Metrology & Measurement Technique, 2022; 49: 44–47. (in Chinese)
[48] Yang B, Wang D, Shen S B, Liu X. Adaptive human tracking for mobile robots based on depth ranging. Computer Engineering and Design, 2024; 45: 896–903. (in Chinese)
[49] Wang Q, Meng Z, Liu H. Review on application of binocular vision technology in field obstacle detection. IOP Conference Series: Materials Science and Engineering, 2020; 806: 012025.
[50] Zhuang P Z, Lin W S. Research on forest target ranging system based on binocular vision. Forest Engineering, 2023; 39(5): 111–117,127.
[51] Hu J T, Gao L, Bai X P, Li T C, Liu X G. Review of research on automatic guidance of agricultural vehicles. Transactions of the CSAE, 2015; 31(10): 1–10. (in Chinese)
[52] Yuan C, Liu J, Wang Y. Research on indoor positioning and navigation method of AGV based on multi-sensor fusion. Highlights in Science, Engineering and Technology, 2022; 7: 206–213.
[53] Guan C, Zhao W, Xu B, Cui Z, Yang Y, Gong Y. Design and experiment of electric uncrewed transport vehicle for solanaceous vegetables in greenhouse. Agriculture, 2025; 15: 118.
[54] Schultz A, Gilabert R, Bharadwaj A, Uijt de Haag M, Zhu Z. A navigation and mapping method for UAS during under-the-canopy forest operations. 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS), Savannah, USA, 30 May 2016. DOI: 10.1109/PLANS.2016.7479768
[55] Liu J, Yuan J, Cai J Y, Tao C L, Wang L M, Cheng W. Autopilot system of agricultural vehicles based on GPS/INS and steer-by-wire. Transactions of the CSAE, 2016; 32(1): 46–53. (in Chinese)
[56] Shentu S Z, Gong Z, Liu X J, Liu Q, Xie F G. Hybrid navigation system based autonomous positioning and path planning for mobile robots. Chinese Journal of Mechanical Engineering, 2022; 35(5): 235–247.
[57] Long T. Positioning and tracking control in navigation of tracked transfer vehicles in hilly mountainous areas. Southwest University, Chongqing, China, 2022. (in Chinese) DOI: 10.27684/d.cnki.gxndx.2022.000746
[58] Li S. Overview of algorithm research on trajectory tracking and control for intelligent vehicles. Automotive Digest, 2023; 9: 19–27. (in Chinese)
[59] Chen R D. Research on trajectory tracking control of autonomous racing car based on PP algorithm. School of Electromechanical Engineering Guangdong University of Technology, Guangdong, China, 2022. (in Chinese) DOI: 10.27029/d.cnki.ggdgu.2022.000085
[60] Wang L H, Shi J C, Wang L G, Jiao Z, Li Y, Chen J, et al. A location and adaptive path tracking method for intelligent harvesters. Journal of Navigation and Positioning, 2020; 8: 29–36. (in Chinese)
[61] Wang R, Li Y, Fan J H, Wang T, Chen X T. A novel pure pursuit algorithm for autonomous vehicles based on salp swarm algorithm and velocity controller. IEEE Access, 2020; 8: 166525–166540.
[62] Xiao S D, Jiang H F, Du J L, Wang Y H, Meng X Y, Xiong Y. Path tracking algorithm of agricultural vehicle based on two stages pure tracking model. Transactions of the CSAM, 2023; 54: 439–446,458. (in Chinese). DOI: 10.6041/j.issn.1000-1298. 2023. 04. 046
[63] Guo B X, Du X L, Tao X S. Algorithm improvement based on pure tracking model. Automobile Applied Technology, 2019; 15: 32–34. (in Chinese)
[64] Liang J. Methods and research progress of path tracking for mobile robot. Sensor World, 2023; 29: 7–14. (in Chinese)
[65] Liang W, Zhai Z Q, Zhu Z X, Mao E R. Path tracking control of an autonomous tractor using improved Stanley controller optimized with multiple-population genetic algorithm. Actuators, 2022; 11: 22.
[66] Cui B B, Sun Y, Ji F, Wei X, Zhu Y, Zhang S. Study on whole field path tracking of agricultural machinery based on fuzzy Stanley model. Transactions of the CSAM, 2022; 53(12): 43–48,88. (in Chinese)
[67] Tang J C. Design and experimental study on key components of a self-following cabbage transporter. Shenyang Agricultural University, Shenyang, China, 2025. (in Chinese) DOI: 10.27327/d.cnki.gshnu.2025.000387.
[68] Sun Y, Cui B B, Ji F, Wei X, Zhu Y. The full-field path tracking of agricultural machinery based on PSO-enhanced fuzzy Stanley model. Applied Sciences, 2022; 12: 7683.
[69] Höffmann M, Patel S, Büskens C. Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques. Journal of Field Robotics, 2024; 41: 823–844.
[70] Yue M, Hou X Q, Gao R J, Chen J. Trajectory tracking control for tractor-trailer vehicles: a coordinated control approach. Nonlinear Dynamics, 2018; 91: 1061–1074.
[71] Zhao S E, Chen W B, Deng Z X, Liu W. Trajectory tracking control for intelligent vehicles driving in curved road based on expanded state observers. Journal of Automotive Safety and Energy, 2022; 13: 112–121. (in Chinese)
[72] Kovacs A, Vajk I. Optimization-based model predictive tube control for autonomous ground vehicles with minimal tuning parameters. Unmanned Systems, 2023; 11: 93–108.
[73] Chen W, Wang S. Four-wheel AGV transporter straight-line movement PID control and implementation. Automation Application, 2024; 65: 94–96, 105. (in Chinese)
[74] Lou M, Xiong S, Sui L, Lu R, Jiang H. Analysis of automatic parking path tracking based on preview PID. Automobile Applied Technology, 2023; 48: 66–71. (in Chinese)
[75] Wang D J, Chen J H, Chen Y, Zheng X K, Wang L, Wang L L. Parking robot path-tracking system based on discrete PID algorithm. Journal of Advanced Computational Intelligence and Intelligent Informatics, 2023; 27: 411–420.
[76] Piao C, Liu X, Lu C. Lateral control using parameter self-tuning LQR on autonomous vehicle. 2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS), Chongqing, China, December 06, 2019. DOI: 10.1109/ICICAS48597.2019.00197
[77] Li H, Li P Q, Yang L K, Zou J, Li Q P. Safety research on stabilization of autonomous vehicles based on improved-LQR control. AIP Advances, 2022; 12: 015313.
[78] Zhou W Q, Zhao Y H, Liu Q C, Chen L. Lateral control strategy of vehicle path tracking based on improved LQR. J. Huazhong Univ. of Sci. & Tech. (Natural Science Edition), 2024; 52: 135–141. (in Chinese)
[79] Liu Y F, Shi G L, Chen Y F, Shi L. Fuzzy path following control method based on pure pursuit model. Machine Design and Research, 2022; 38: 136–140,157. (in Chinese)
[80] Zhang C L, Gao G L, Zhao C Z, Li L, Li C, Chen X. Research on 4WS agricultural machine path tracking algorithm based on fuzzy control pure tracking model. Machines, 2022; 10: 597.
[81] Wang Z H, Xun Y, Wang Y K, Yang Q H. Review of smart robots for fruit and vegetable picking in agriculture. Int J Agric & Biol Eng, 2022; 15(1): 33–54.
[82] Rajendran V S, Debnath B, Mghames S, Mandil W, Parsa S, Parsons S, et al. Towards autonomous selective harvesting: A review of robot perception, robot design, motion planning and control. Journal of Field Robotics, 2024; 41: 2247–2279.
[83] Jin Y C, Liu J Z, Xu Z J, Yuan S Q, Li P P, Wang J Z. Development status and trend of agricultural robot technology. Int J Agric & Biol Eng, 2021; 14(4): 1–19.
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