Complete coverage path planning of irregular convex field for the high clearance unmanned sprayer based on improved particle swarm optimizer algorithm

LIU Guohai; WAN Yalian; SHEN Yue; LIU Hui; HE Siwei; ZHANG Yafei

doi:10.7671/j.issn.1001-411X.202409017

Journal of South China Agricultural University > 2025 > 46(3): 390-398. > DOI: 10.7671/j.issn.1001-411X.202409017

LIU Guohai, WAN Yalian, SHEN Yue, et al. Complete coverage path planning of irregular convex field for the high clearance unmanned sprayer based on improved particle swarm optimizer algorithm[J]. Journal of South China Agricultural University, 2025, 46(3): 390-398. DOI: 10.7671/j.issn.1001-411X.202409017

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Complete coverage path planning of irregular convex field for the high clearance unmanned sprayer based on improved particle swarm optimizer algorithm

School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China

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Received Date: September 12, 2024
Available Online: March 12, 2025
Published Date: February 27, 2025

Graphical Abstract

Abstract

Abstract

Objective
In order to meet the application requirements of autonomous navigation full-coverage operation of high clearance unmanned sprayers and optimize the efficiency of agricultural machine operation.
Method
A complete coverage traversal path planning algorithm for irregular convex fields was proposed. Firstly, an boundary contour model of irregularly convex field was obtained based on the boundary data of farmland area. Secondly, on the basis of the traditional U-turn pattern, the angle between the operation rows and the field boundaries was introduced to elaborate the principles of articulated paths between the operation rows in detail. After generating complete coverage operation rows with random direction angles by parallel line offset from the straight line passing through the center point of the irregular convex region, the direction angles of the operation rows were optimized by the improved particle swarm optimizer (PSO) algorithm, and the field traversal complete coverage working paths were generated. Finally, the algorithm was tested through simulations on four typical real-world fields.
Result
Compared with traditional path planning algorithms, the proposed algorithm reduced the total traversal distance by 9.01, 23.25, 8.71 and 14.32 m in fields 1 to 4, respectively. The reduction rates of the number of turns were 11.1%, 61.5%, 16.7% and 5.3%, while the additional coverage rates decreased by 0.20, 0.96, 0.45 and 1.96 percentage points, respectively. These improvements effectively reduced the energy consumption of unmanned agricultural machinery and enhanced operational efficiency.
Conclusion
Under the premise of complete coverage for the operation area, the proposed algorithm can generate operation paths for unmanned agricultural machinery with shorter travel distances, higher coverage rates and fewer turns. This provides a theoretical support for the development of path planning technology for unmanned agricultural machinery.

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References (29)

References

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Complete coverage path planning of irregular convex field for the high clearance unmanned sprayer based on improved particle swarm optimizer algorithm

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