In-field path planning method for soil compaction reduction by returning soil to the field

By dividing the fields using multispectral remote sensing and deep learning models, and combining particle swarm optimization algorithms to plan the path of the fertilization machine, the problem of neglecting soil compaction in traditional fertilization machine path planning is solved. This reduces the area of ​​furrow compaction and the number of repeated compaction cycles, thereby improving the soil improvement effect.

CN121140829BActive Publication Date: 2026-05-26NORTHEAST AGRICULTURAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NORTHEAST AGRICULTURAL UNIVERSITY
Filing Date
2025-09-26
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Traditional straw return machines neglect the cumulative effect of soil compaction in their path planning, which causes the soil improvement effect of straw return to the field to be partially offset or even exacerbate the risk of soil degradation.

Method used

Multispectral remote sensing technology and deep learning models were used to divide the fields into plots. Particle swarm optimization algorithm was combined to plan the path of the fertilization machine to reduce the area of ​​furrow compaction and the number of repeated compaction times. The path was optimized by objective function to ensure the shortest path while reducing soil structure damage.

Benefits of technology

While ensuring the efficiency of straw return to the field, we aim to minimize the damage to soil structure caused by mechanical operations, achieve the dual goals of "returning straw to the field" and "preserving soil," and provide technical support for smart agriculture.

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Abstract

This application presents a field path planning method for soil compaction reduction using a soil-repairing machine, addressing the problem of improving soil improvement effects during path planning and belonging to the field of agricultural machinery scheduling. The method includes: acquiring multispectral remote sensing images of the field, processing them to obtain images of each field; inputting each field image into a pre-trained operational area classification model to obtain the category of each field, including ordinary areas, compaction-sensitive areas, and areas without straw obstruction; and performing path planning based on the location and category of each field, using path length, compaction area of ​​sensitive areas, and number of compaction cycles in sensitive areas as objective functions. This application combines soil compaction with particle swarm optimization algorithms, proposing a novel soil-repairing machine path planning strategy that can reduce furrow compaction area and repeated compaction cycles while ensuring the shortest path within the field, achieving the dual goals of soil improvement and soil protection.
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