Path Planning for Full Coverage of Farmland Operations in Hilly and Mountainous Areas Based on the Dung Beetle Optimization Algorithm
Xinlan Lin, Jin Yan, Huamin Du, Fujun Zhou · Applied Sciences · 2025
This study aims to address the issues of full-coverage path planning in single fields and optimal traversal order in multi-fields in hilly, mountainous areas. To this end, it proposes a full-coverage path planning method based on an improved DBO algorithm. Using the digital elevation model to construct the farmland model, the energy consumption model is introduced into single-field planning to determine the optimal operating direction angle for full-coverage path planning with optimal energy consumption. To address the issues of the traditional DBO algorithm easily falling into a local optimum and the lack of information interaction among populations, a multi-strategy improved DBO algorithm is proposed to determine the optimal traversal sequence for multiple fields. Tent chaotic mapping is used to initialize the population and the Osprey optimization algorithm and adaptive T-perturbation distribution strategy are integrated to enhance the foraging behavior of small dung beetles. This gives the algorithm good global exploration capabilities in the initial stage and strong local exploitation capabilities in the later stage. The simulation results show that the total energy consumption of energy-optimal path planning is 5.62 × 104 J, which is 19.93% less than the optimal path length. The traversal order solved by the improved DBO algorithm saves 9.2% more energy than the original algorithm, demonstrating a significant energy-saving effect.