Path Planning for Autonomous Land-Levelling Operations Based on an Improved ACO

作者：Wenming Chen, Xinhua Wei, Qi Song, Lei Sun, Yuheng Zheng, Chengqian Jin, Chengliang Liu, Shanlin Yi, Ziyu Zhu, Chenyang Li, Shuai Xu, Dongdong Du, Shaocen Zhang · 发表于：Agronomy · 年份：2026 · DOI：10.3390/agronomy16070700 · 被引用次数：1 · 研究领域：Geotechnical Engineering and Analysis、Geotechnical Engineering and Soil Stabilization、Geodetic Measurements and Engineering Structures

This study proposes a variable-scale optimization strategy for land-levelling path planning to overcome the limitations of conventional traversal-based operations, including poor coordination, insufficient planning, low operational efficiency, and the computational burden associated with large datasets and constrained earthmoving capacity. For large-scale inter-regional earthwork balancing, an improved ant colony optimization (IACO) algorithm is developed to generate efficient region to region transfer routes. After verifying that inter-regional earthwork balance satisfies the levelling requirement, a field-wide fine-levelling plan is produced at the grid scale using a hybrid method that integrates an improved A* search with ant colony optimization (FIA*ACO). The proposed framework is evaluated through simulation and field experiments using measurement-based indicators, including the maximum elevation difference and the proportion of points within ±5 cm of the target elevation. Field results show that IACO-based inter-regional planning increases the ±5 cm compliant proportion by 14.18 percentage points and reduces the maximum elevation difference by 0.079 m. Subsequent FIA*ACO-based fine-gridded planning further improves the ±5 cm compliant proportion by 20.82 percentage points and decreases the maximum elevation difference by 0.311 m. Overall, the results demonstrate that inter-regional planning rapidly expands the area meeting levelling standards, while grid-level refinemen...