Modeling of working environment and coverage path planning method of combine harvesters
Keywords:
combine harvester, environmental modeling, path planning, farmland turningAbstract
This paper mainly studied the working environment modeling and coverage path planning of combine harvesters. The boundaries of the farmland to be harvested were extracted through the farmland satellite imagery and canny algorithm. The polygon approximation method was used to fit the extracted boundaries as polygons. The edge offset of the farmland and obstacles was realized based on the principle of straight skeleton. According to the structure data of the split points which were obtained through the improved scan line algorithm, the coverage path planning of the combine harvester was realized. Moreover, the circular arc transition algorithm was used to optimize the harvesting paths to achieve the smooth turning of the combine harvester at the edge of farmland and when encountering obstacles. The simulation results show that the proposed the proposed polygon approximation method can accurately depict the boundaries of the farmland to be harvested, and reduce the amount of data to be stored. Additionally, the designed path planning method can realize the coverage path planning of the combine harvester in irregular and internal obstacle farmland. Keywords: combine harvester, environmental modeling, path planning, farmland turning DOI: 10.25165/j.ijabe.20201302.5210 Citation: Lu E, Xu L Z, Li Y M, Tang Z, Ma Z. Modeling of working environment and coverage path planning method of combine harvesters. Int J Agric & Biol Eng, 2020; 13(2): 132–137.References
[1] Yin X, Du J, Noguchi N, Yang T X, Jin C Q. Development of autonomous navigation system for rice transplanter. Int J Agric & Biol Eng, 2018; 11(6): 89–94.
[2] Luo C M, Li W, Fan X N, Yang H, Ni J J, Zhang X W, et al. Positioning technology of mobile vehicle using self-repairing heterogeneous sensor networks. Journal of Network and Computer Applications, 2017; 93, 110–122.
[3] Dou W H, Zhu K, Liang S H, Wen W S, Guo Y, Tan Y. Path planning algorithm of field robot based on topological map and robot control. China Sciencepaper, 2016; 11(22): 2525–2530.
[4] Rahman M M, Ishii K, Noguchi N. Optimum harvesting area of convex and concave polygon field for path planning of robot combine harvester. Intelligent Service Robotics, 2019; 12(2): 167–179.
[5] 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.
[6] Korkmaz S A, Poyraz M. Path planning for rescue vehicles via segmented satellite disaster images and GPS road map. International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.
[7] Zhao D A, Luo J, Sun Y P, Hong J Q, Zhang J. Design and experiment of navigation control system of automatic operation boat in river crab culture. Transactions of the CSAE, 2016; 32(11): 181–188. (in Chinese)
[8] Liu G, Kang X, Xia Y X, et al. Global path planning algorithm and experiment based on GNSS-controlled precise land leveling system. Transactions of the CSAM, 2018; 49(5): 27–33. (in Chinese)
[9] Patle B K, Ganesh B L, Pandey A, Parhi D R K, Jagadeesh A. A review: On path planning strategies for navigation of mobile robot. Defence Technology, 2019; 15(4): 582–606.
[10] Oksanen T, Visala A. Path planning algorithms for agricultural machines. Journal of Field Robotics, 2010; 26(8): 651–668.
[11] Zhou K, Leck Jensen A, Sørensen C G, Busato P, Bothtis D D. Agricultural operations planning in fields with multiple obstacle areas. Computers and Electronics in Agriculture, 2014; 109: 12–22.
[12] Zhu D Q, Tian C, Sun B, Luo C M. Complete coverage path planning of autonomous underwater vehicle based on GBNN algorithm. Journal of Intelligent & Robotic Systems, 2018; 94: 237–249.
[13] Zhang C B, Wang X S. Complete coverage path planning based on ant colony algorithm. China Mechanical Engineering, 2008; 19(16): 1945–1949. (in Chinese)
[14] Tang D L, Yuan B, Hu L, Li M Y, Wei Z B. Complete coverage path planning method for oil tank inspection wall climbing robot. Journal of Engineering Design, 2018; 25(3): 253–261. (in Chinese)
[15] Bhattacharya S, Ghrist R, Kumar V. Persistent homology for path planning in uncertain environments. IEEE Transactions on Robotics, 2015; 31(3): 578–590.
[16] Rami A J, Mohammad A J, Hubert R. A novel edge detection algorithm for mobile robot path planning. Journal of Robotics, 2018; 9: 1–12.
[17] Prasad D K, Leung M K H. Polygonal representation of digital curves. Digital Image Processing, InTech, 2012; pp.71–90.
[18] Luo H, Li D C, Xie R D, Cao Y. An algorithm of contour offsetting based on the principle of straight skeleton for rapid prototyping. Journal of Computer-Aided Design & Computer Graphics, 2011; 23(11): 1908–1914.
[19] Räisänen V. Peltorobotin reititys “siksak”-täytöllä. Tampere University of Technology, 2008.
[20] Saad M, Maher M L. Shared understanding in computer-supported collaborative design. Computer Aided Design, 1996; 28(3): 183–192.
[21] Rahman M M, Ishii K. Heading estimation of robot combine harvesters during turning maneuveres. Sensors, 2018; 18(5): 1390.
[2] Luo C M, Li W, Fan X N, Yang H, Ni J J, Zhang X W, et al. Positioning technology of mobile vehicle using self-repairing heterogeneous sensor networks. Journal of Network and Computer Applications, 2017; 93, 110–122.
[3] Dou W H, Zhu K, Liang S H, Wen W S, Guo Y, Tan Y. Path planning algorithm of field robot based on topological map and robot control. China Sciencepaper, 2016; 11(22): 2525–2530.
[4] Rahman M M, Ishii K, Noguchi N. Optimum harvesting area of convex and concave polygon field for path planning of robot combine harvester. Intelligent Service Robotics, 2019; 12(2): 167–179.
[5] 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.
[6] Korkmaz S A, Poyraz M. Path planning for rescue vehicles via segmented satellite disaster images and GPS road map. International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.
[7] Zhao D A, Luo J, Sun Y P, Hong J Q, Zhang J. Design and experiment of navigation control system of automatic operation boat in river crab culture. Transactions of the CSAE, 2016; 32(11): 181–188. (in Chinese)
[8] Liu G, Kang X, Xia Y X, et al. Global path planning algorithm and experiment based on GNSS-controlled precise land leveling system. Transactions of the CSAM, 2018; 49(5): 27–33. (in Chinese)
[9] Patle B K, Ganesh B L, Pandey A, Parhi D R K, Jagadeesh A. A review: On path planning strategies for navigation of mobile robot. Defence Technology, 2019; 15(4): 582–606.
[10] Oksanen T, Visala A. Path planning algorithms for agricultural machines. Journal of Field Robotics, 2010; 26(8): 651–668.
[11] Zhou K, Leck Jensen A, Sørensen C G, Busato P, Bothtis D D. Agricultural operations planning in fields with multiple obstacle areas. Computers and Electronics in Agriculture, 2014; 109: 12–22.
[12] Zhu D Q, Tian C, Sun B, Luo C M. Complete coverage path planning of autonomous underwater vehicle based on GBNN algorithm. Journal of Intelligent & Robotic Systems, 2018; 94: 237–249.
[13] Zhang C B, Wang X S. Complete coverage path planning based on ant colony algorithm. China Mechanical Engineering, 2008; 19(16): 1945–1949. (in Chinese)
[14] Tang D L, Yuan B, Hu L, Li M Y, Wei Z B. Complete coverage path planning method for oil tank inspection wall climbing robot. Journal of Engineering Design, 2018; 25(3): 253–261. (in Chinese)
[15] Bhattacharya S, Ghrist R, Kumar V. Persistent homology for path planning in uncertain environments. IEEE Transactions on Robotics, 2015; 31(3): 578–590.
[16] Rami A J, Mohammad A J, Hubert R. A novel edge detection algorithm for mobile robot path planning. Journal of Robotics, 2018; 9: 1–12.
[17] Prasad D K, Leung M K H. Polygonal representation of digital curves. Digital Image Processing, InTech, 2012; pp.71–90.
[18] Luo H, Li D C, Xie R D, Cao Y. An algorithm of contour offsetting based on the principle of straight skeleton for rapid prototyping. Journal of Computer-Aided Design & Computer Graphics, 2011; 23(11): 1908–1914.
[19] Räisänen V. Peltorobotin reititys “siksak”-täytöllä. Tampere University of Technology, 2008.
[20] Saad M, Maher M L. Shared understanding in computer-supported collaborative design. Computer Aided Design, 1996; 28(3): 183–192.
[21] Rahman M M, Ishii K. Heading estimation of robot combine harvesters during turning maneuveres. Sensors, 2018; 18(5): 1390.
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Published
2020-04-10
How to Cite
Lu, E., Xu, L., Li, Y., Tang, Z., & Ma, Z. (2020). Modeling of working environment and coverage path planning method of combine harvesters. International Journal of Agricultural and Biological Engineering, 13(2), 132–137. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/5210
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Power and Machinery Systems
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