Enhanced Path Planning for Facility Agriculture Operation Platforms: A Hybrid Approach Utilizing Improved A* and DFS Algorithms

Highlights A dynamic weighted heuristic function is used to enhance the computing efficiency of algorithms. An improved neighborhood searching method is employed to mitigate computational waste. A node optimization method is utilized to achieve smoother path generation. The improved Depth First Search algorithm is applied to optimize articulation paths of the facility's operating areas. Abstract. Compared to traditional agricultural environments, facility-based agricultural environments are spatially compact and poorly signalized, making it difficult to realize accurate navigation operations. At the same time, the complexity of interfacing the different operational areas within the facility has resulted in unnecessary paths for the platform during regional transitions. To tackle these challenges, this study designs an autonomous navigation mobile platform suitable for working in a facility environment. Then, we implement a dynamic weighted heuristic function and an optimized search neighborhood direction for the global path planning in A* algorithm to improve the computational efficiency. The simulation results using MATLAB R2021a software show that the improved algorithm efficiency has increased by 30%. Furthermore, we use the Depth First Search (DFS) algorithm to reduce the total distance of articulation, smooth the path by optimizing the number of nodes, and verify the integration algorithm through simulation. Finally, field experiment is conducted and the results show that the computation time is reduced by 30%, the number of critical nodes is reduced by 50%, the operations coverage ratio and operations distance ratio are also increased by 7.9% and 8.6%, respectively, when applying the improved A* and DFS algorithm, which meets the requirements of the facility environment operations. Keywords: DFS algorithm, Facility agriculture operations, Improved A* algorithm, Path planning, Pathway linkage.

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Publication Details

Journal
Applied Engineering in Agriculture
Published
2025-01-01
DOI
https://doi.org/10.13031/aea.16323
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Enhanced Path Planning for Facility Agriculture Operation Platforms: A Hybrid Approach Utilizing Improved A* and DFS Algorithms

Hong Miao, Xin Ji, Sixing Liu, Mingmiao Liu et al.
Applied Engineering in Agriculture
Robotic Path Planning Algorithms
article

Enhanced Path Planning for Facility Agriculture Operation Platforms: A Hybrid Approach Utilizing Improved A* and DFS Algorithms

Hong Miao, Xin Ji, Sixing Liu, Mingmiao Liu, Tianhong Liu, Zechen Zhang, Yingying Wang, Yanjun Zhang, Shanwen Zhang, Yan Chai
article en

Abstract

Highlights A dynamic weighted heuristic function is used to enhance the computing efficiency of algorithms. An improved neighborhood searching method is employed to mitigate computational waste. A node optimization method is utilized to achieve smoother path generation. The improved Depth First Search algorithm is applied to optimize articulation paths of the facility's operating areas. Abstract. Compared to traditional agricultural environments, facility-based agricultural environments are spatially compact and poorly signalized, making it difficult to realize accurate navigation operations. At the same time, the complexity of interfacing the different operational areas within the facility has resulted in unnecessary paths for the platform during regional transitions. To tackle these challenges, this study designs an autonomous navigation mobile platform suitable for working in a facility environment. Then, we implement a dynamic weighted heuristic function and an optimized search neighborhood direction for the global path planning in A* algorithm to improve the computational efficiency. The simulation results using MATLAB R2021a software show that the improved algorithm efficiency has increased by 30%. Furthermore, we use the Depth First Search (DFS) algorithm to reduce the total distance of articulation, smooth the path by optimizing the number of nodes, and verify the integration algorithm through simulation. Finally, field experiment is conducted and the results show that the computation time is reduced by 30%, the number of critical nodes is reduced by 50%, the operations coverage ratio and operations distance ratio are also increased by 7.9% and 8.6%, respectively, when applying the improved A* and DFS algorithm, which meets the requirements of the facility environment operations. Keywords: DFS algorithm, Facility agriculture operations, Improved A* algorithm, Path planning, Pathway linkage.

Applied Engineering in AgricultureVol. 41(3)
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Openalex Percentile: Top 88%
Robotic Path Planning Algorithms
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