Abstract
The study introduces an energy-efficient coverage path planning with tree bypassing navigation in hilly Camellia oleifera orchards. Firstly, a 3D grid map incorporating elevation was built to segment the workspace into rectangular flat and uneven sub-regions. Furthermore, an energy consumption model of the multifunctional platform for Camellia oleifera was developed. Secondly, to improve the energy efficiency, a long-edge row-wise strategy featuring tree bypassing was proposed for the flat sub-regions, with an improved A* ensuring efficient dead-end escape. For the uneven sub-regions, the terrain coverage was achieved through integrating contour-following and tree-bypassing arcs. Finally, a Manhattan-distance fitness function minimized inter-region travel, with optimal sequences and entries determined by a hybrid Genetic Algorithm and Tabu Search. Based on the results of algorithm simulations under convex slope, uniform slope, and slope-pit mixed terrains, the performance of the proposed energy-efficient coverage path planning model were evaluated in comparison with Greedy Genetic, Greedy, Spiral, and Boustrophedon algorithms. The results showed that the average pitch angle of the proposed algorithm was reduced by 75.00%, 75.68%, 71.88%, and 81.21% compared to Greedy Genetic, Greedy, Spiral, and Boustrophedon algorithms, respectively. Specifically, on the convex slope terrain, the proposed model obtained a total energy reduction of 14.46%, 12.41%, 6.8%, and 18.20% compared to the aforementioned algorithms, respectively. For the uniform slope terrain and the slope-pit mixed terrain, the reduction percentages were 1.71%, 2.3%, 13.42%, 25.74% and 11.2%, 11.12%, 14.29%, 14.47%, respectively. The results confirm that the proposed model has superior adaptability and energy efficiency in covering diverse terrain types.
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