Unloading method in coordinated harvesting

Authors

  • Xiaoxiong Wang 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
  • Zhihong Man 3. School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC3122, Australia http://orcid.org/0000-0002-8338-2125
  • Zhuo Wang 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
  • Xiaoping Bai 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
  • Jian Wang 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
  • Zhikang Ge 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China

DOI:

https://doi.org/10.25165/ijabe.v18i2.8863

Keywords:

coordinated harvesting, loading uniformity, overflow algorithm, path planning

Abstract

In this study, a novel unloading method was developed for the operation of the unloading spout during the loading process in a master-slave automatic harvesting system. It demonstrated that uniform and full loading in the grain tank can be achieved by uninterrupted unloading with the motion of the unloading spout. First, the overflow algorithm is proposed to divide the loading process into multiple loading rounds. In each round, a specific loading area and target loading height are assigned to achieve better uniformity. Subsequently, complete coverage path planning and transfer path planning algorithms are developed to guide the motion of the unloading spout during different loading rounds. With the motion of the unloading spout, loading can be carried out accurately to maximize the capacity utilization of the grain tank, which can reduce the round-trip frequency of the transport vehicle and improve the energy and time efficiency of the harvesting operation. Simulation results are provided to validate the excellent performance of the presented unloading method. Key words: coordinated harvesting; loading uniformity; overflow algorithm; path planning DOI: 10.25165/j.ijabe.20251802.8863 Citation: Wang X X, Man Z H, Wang Z, Bai X P, Wang J, Ge Z K. Unloading method in coordinated harvesting. Int J Agric & Biol Eng, 2025; 18(2): 45–54.

References

Alexandratos N, Bruinsma J. World agriculture towards 2030/2050: the 2012 revision. 2012.

Wang K R, Xie R Z, Xue J, Sun L R, Li S K. Comparison and analysis of maize grain commodity quality and mechanical harvest quality between China and the United States. Int J Agric & Biol Eng, 2022; 15(1): 55–61.

Wang Z T, Tang Y R, Jin X Z, Liu Y, Zhang H, Niu H, et al. Comprehensive evaluation of Korla fragrant pears and optimization of plucking time during the harvest period. Int J Agric & Biol Eng, 2022; 15(3): 242–250.

Zhang L, Zhang H D, Chen Y D, Dai S H, Li X M, Imou K, Liu Z H, et al. Real-time monitoring of optimum timing for harvesting fresh tea leaves based on machine vision. Int J Agric & Biol Eng, 2019; 12(1): 6–9.

Kurita H, Iida M, Suguri M, Masuda R. Application of image processing technology for unloading automation of robotic head-feeding combine harvester. Engineering in Agriculture, Environment and Food, 2012; 5(4): 146–151.

Kurita H, Iida M, Suguri M, Masuda R, Cho W. Efficient searching for grain storage container by combine robot. Engineering in Agriculture, Environment and Food, 2014; 7(3): 109–114.

Kurita H, Iida M, Cho W, Suguri M. Rice autonomous harvesting: operation framework. Journal of Field Robotics, 2017; 34(6): 1084–1099.

Delchev N, Trendafilov K. Structural analysis of the operations and time for tank unloading of grain harvesters. International Journal of Science and Research, 2015; 4(3): 1890–1894.

Tihanov G. A study on the hopper unloading duration of the harvesting machine at different technical parameters. Agricultural Science and Technology, 2020; 12(2): 140–143.

Trendafilov K, Delchev N, Kolev B, Tihanov G. Study on the emptying time of grain harvester hoppers. Agricultural Science and Technology, 2017; 9(4): 291–295.

Reinecke M, Grothaus H P, Hembach G, Scheuren S, Hartanto R Dynamic and distributed infield-planning system for harvesting. In: 2013 ASABE Conference, Kansas City, Missouri, July 21-24, 2013. https://elibrary.asabe.org/abstract.asp?aid=43639&t=5

Zhang W, Zhang Z, Luo X, He J, Hu L, Yue B. Position-velocity coupling control method and experiments for longitudinal relative position of harvester and grain truck. Transactions of the CSAE, 2021; 37(9): 1–11. (in Chinese)

Delchev N, Trendafilov K, Tihanov G, Stoyanov Y. Grain combines productivity according to various unloading methods - in the field and at the edge of the field. Agricultural Science and Technology, 2016; 8(3): 221–226.

Liu D, Wang Z, Bai X, Zhao Y. Grain truck loading status detection based on machine vision. In 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), Xiamen, China, 2019. doi: 10.1109/ICIVC47709.2019.8981112

Liu L, Du Y, Li X, Sun T, Zhang W, Li G, Mao E. An automatic forage unloading method based on machine vision and material accumulation model. Computers and Electronics in Agriculture, 2023; 208: 107770.

Liu Z, Dhamankar S, Evans J T, Allen C M, Jiang C, Shaver G M, McDonald B M. Development and experimental validation of a system for agricultural grain unloading-on-the-go. Computers and Electronics in Agriculture, 2022; 198: 107005.

Wang X, Wang Z, Bai X, Ge Z, Zhao Y. Dynamic uniform loading method of grain box of transport vehicle based on three-dimensional point cloud. Transactions of the CSAM, 2022; 53(6): 129–139. (in Chinese)

Ma Z, Chong K, Ma S, Fu W, Yin Y, Yu H, Zhao C. Control strategy of grain truck following operation considering variable loads and control delay. Agriculture, 2022; 12(10): 1545.

Shojaei K. Coordinated saturated output-feedback control of an autonomous tractor-trailer and a combine harvester in crop-harvesting operation. IEEE Transactions on Vehicular Technology, 2022; 71(2): 1224–1236.

Zhang X, Geimer M, Noack P O, Grandl L. Development of an intelligent master-slave system between agricultural vehicles. In IEEE Intelligent Vehicles Symposium (IV), San Diego, CA, 2010. doi: 10.1109/IVS.2010.5548056

Wang X, Wang Z, Bai X, Ge Z, Wang J, Man Z. A loading path planning method for co-loading in automatic harvesting system. In 2023 International Conference on Advanced Mechatronic Systems (ICAMechS), Melbourne, Australia, 2023. doi: 10.1109/ICAMechS59878.2023.10272697

Galceran E, Carreras M. A survey on coverage path planning for robotics. Robotics and Autonomous Systems, 2013; 61(12): 1258–1276.

Liu L, Wang X, Yang X, Liu H, Li J, Wang P. Path planning techniques for mobile robots: Review and prospect. Expert Systems with Applications, 2023; 227: 120254.

Glasius R, Komoda A, Gielen S. A biologically inspired neural net for trajectory formation and obstacle avoidance. Biological Cybernetics, 1996; 74(6): 511–520.

Muthugala M A V J, Samarakoon S M B P, Elara M R. Toward energy-efficient online complete coverage path planning of a ship hull maintenance robot based on glasius bio-inspired neural network. Expert Systems with Applications, 2022; 187: 115940.

Sun B, Zhu D, Tian C, Luo C. Complete coverage autonomous underwater vehicles path planning based on Glasius bio-inspired neural network algorithm for discrete and centralized programming. IEEE Transactions on Cognitive and Developmental Systems, 2019; 11(1): 73–84.

Zhu D, Tian C, Sun B, Luo C. Complete coverage path planning of autonomous underwater vehicle based on GBNN algorithm. Journal of Intelligent & Robotic Systems, 2018; 94(1): 237–249.

Hart P E, Nilsson N J, Raphael B. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 1968; 4(2): 100–107.

Downloads

Published

2025-04-25

How to Cite

Wang, X., Man, Z., Wang, Z., Bai, X., Wang, J., & Ge, Z. (2025). Unloading method in coordinated harvesting. International Journal of Agricultural and Biological Engineering, 18(2), 45–54. https://doi.org/10.25165/ijabe.v18i2.8863

Issue

Vol. 18 No. 2 (2025): IJABE

Section

Applied Science, Engineering and Technology

License

IJABE is an international peer reviewed open access journal, adopting Creative Commons Copyright Notices as follows.


Authors who publish with this journal agree to the following terms:


  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).