Development of Agricultural Machinery Operation Path Planning Algorithms and Mobile Software for Unmanned Rice Oil Rape Rotation Farms

HUANG Xiaomao, WANG Shaoshuai, SHI Yize, HUANG Xiya, MA Yongsheng, LUO Chengming

Abstract

Unmanned farm will be the ultimate form of rice and oil rape cultivation in the rice oil rape rotation area in the middle and lower reaches of the Yangtze River in China. By analyzing the production mode, implement type and operation path planning requirements of unmanned farming in rice and oil rape rotation, intelligent farm implement operation and maintenance software for unmanned farming was designed based on the Android application framework, including modules of plot management, implement attribute management and path planning for the path requirements of the field operation process of typical operation links of unmanned farming for rice and oil rape rotation cultivation. On the basis of the existing algorithms of the group, focusing on designing algorithms for operation path planning in two typical processes, namely integrated rice harvesting and rapeseed sowing and paddy ploughing, and the field operation path planning algorithms coded in Python beforehand was called through the mixed programming of Chaquopy plug-in. The results of simulation test and field test showed that the designed and developed Android software was stable and reliable, with good human computer interaction, and path planning algorithms were able to provide effective operation paths for different implements and common quadrilateral plots, and the operation time of the single field operation path planning algorithm ranged from 29 ms to 1 898 ms, and the computational efficiency and rationality of the paths met the needs of unmanned production of typical operation links in the real application. The computational efficiency and path reasonableness met the needs of unmanned production in typical operations, providing theoretical and technical support for the construction of unmanned farms in the middle and lower reaches of the Yangtze River for rice and oil rape rotations.

 

Keywords: unmanned farm, rice oil rape rotation, path planning, automatic navigation, Android platform

 

Download Full Text:

PDF


References


LI Daoliang, LI Zhen. System analysis and development prospect of unmanned farming[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(7); 1 - 12.

LUO Xiwen, LIAO Juan, HU Lian, et al. Research progress of intelligent agricultural machinery and practice of unmanned farm in China J . Journal of South China Agricultural University, 2021 , 42(6) ; 8 - 17.

LIU Chengliang, LIN Hongzhen, LI Yanming, et al. Analysis on status and development trend of intelligent control technology for agricultural equipment [J]. Transactions of the Chinese Society for Agricultural Machinery, 2020,51 (1) : 1 —18.

ZHAO Bo, ZHANG Weipeng, YUAN Yanwei, et al. Research progress in information technology for agricultural equipment maintenance and operation service management[J] . Transactions of the Chinese Society for Agricultural Machinery, 2023,54 (12): 1 -26.

LUO Xiwen, LIAO Juan, ZANG Ying, et al. Developing from mechanized to smart agricultural production in China [J]. Strategic Study of CAE, 2020, 24(1) : 46 -54.

ZHOU Jun, HE Yongqiang. Research progress on navigation path planning of agricultural machinery) [J]. Transactions of the Chinese Society for Agricultural Machinery, 2021 , 52(9) ; 1-14. (in Chinese)

RAHM AN M, ISHI1 K, NOGUCHI N. Optimum harvesting area of convex and concave polygon field for path planning of robot combine harvesterf [J] . Intelligent Service Robotics, 2019, 12(2) ; 167 - 179.

HAN X, KIM H J, JEON С W, et al. Design and field testing of a polygonal paddy infield path planner for unmanned tillage operations [J]. Computers and Electronics in Agriculture, 2021 , 191 ; 106567.

ZHAI Weixin, WANG Dongxu, CHEN Zhibo, et al. Autonomous operation path planning method for unmanned agricultural machinery [ J]. Transactions of the CSAE, 2021, 37 (16): 1 —7.

BOCHTIS D D, S0RENSEN С G, BUSATO P, et al. Benefits from optimal route planning based on B-patterns [J]. Biosystems Engineering, 2013, 115(4): 389 -395.

SEYYEDHASANI H, DVORAK J S. Using the vehicle routing problem to reduce field completion times with multiple machines .[ J]. Computers and Electronics in Agriculture, 2017, 134; 142 - 150.

EVANS IV J T, PITLA S K, LUCK J D, et al. How crop grain harvester path optimization in headland patterns [J]. Computers and Electronics in Agriculture, 2020, 171 ; 105295.

ZHOU Chenlin, WANG Xiaochan, HE Ruiyin, et al. Matching model and analysis of harvester operation routes and plot conditions [ J ]. Acta Agriculturae Universitatis Jiangxiensis, 2022, 44(4); 1023 - 1033. (in Chinese)

J1NG Yunpeng, JIN Zhikun, LIU Gang. Three dimensional path planning method for navigation of farmland leveling based on improved ant colony algorithm[ J j. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51 (Supp. 1) ; 333 - 339.

ZHANG Fan, LUO Xiwen, ZHANG Zhigang, et al. Agricultural machinery scheduling optimization method based on improved multi-parents genetic algorithm. Transactions of the CSAE, 2021 , 37(9) ; 192 - 198. (in Chinese)

CHEN Kai, XIE Yinshan, LI Yanming, et al. Full coverage path planning method of agricultural machinery under multiple constraints [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(5) ; 17 -26,43. (in Chinese)

HAO Kun, ZHANG Huijie, LI Zhisheng, et al. Path planning of mobile robot based on improved obstacle avoidance strategy and double optimization ant colony algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(8): 303 -312,422.


Refbacks

  • There are currently no refbacks.