Optimizing the Path of Plug Tray Seedling Transplanting by Using the Improved A* Algorithm

Xiaojun Li, Weibing Wang (), Ganghui Liu, Runze Li and Fei Li
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Xiaojun Li: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Weibing Wang: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Ganghui Liu: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Runze Li: College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Fei Li: College of Mechanical Engineering and Automation, Beihang University, Beijing 100083, China

Agriculture, 2022, vol. 12, issue 9, 1-22

Abstract: In greenhouse nurseries, one of the important tasks of the automatic transplanter is replanting missing or bad seedling holes with healthy seedlings. This requires the transplanter to spend significant time moving between the supply trays and target trays during replanting. The diversity and complexity of the transplanting routes affect transplanter efficiency. Path planning method can find a better path for the manipulator and improve the efficiency of transplantation. The A* algorithm (A*), which is one of the optimal path search algorithms, is often used in practical applications of path planning. In this paper, the heuristic function of the A* is optimized by the ant colony algorithm (ACA), and an improved A* algorithm (Imp-A*) is obtained. Simulation tests and transplanting trials of Imp-A*, A*, ACA, Dijkstra (DA), and common sequence method (CSM) were carried out using 32-, 50-, 72-, and 128-hole plug trays. The results show that Imp-A* inherits the advantages of A* and ACA in terms of path planning length and computation time. Compared to A*, ACA, DA, and CSM, the transplanting time for Imp-A* was reduced by 2.4%, 12.84%, 11.63%, and 14.27%, respectively. In just six trays of transplanting tasks, Imp-A* saves 60.91 s compared to CSM, with an average time saving of 10.15 s per tray. The combination optimization algorithm has similar application prospects in agriculture.

Keywords: greenhouse; replanting; seedlings; path planning; optimization algorithms (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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