Path planning for field full coverage operation in hilly and mountainous farmlands based on the enhanced whale optimization algorithm

Comprehensive path planning can greatly contribute to the single plots and optimal traversal order for multiple plots in the hilly and mountainous regions. It is very necessary to enhance the operational quality and energy efficiency of agricultural machinery. In this study, path planning was designed using an improved whale optimization algorithm (IWOA). Firstly, the digital elevation model (DEM) of the operation area was obtained using electronic maps. ArcMap software was used to perform the vector clipping on the DEM data, in order to extract the latitude and longitude information of the operation area, thereby constructing and mapping the plot models. The entire operation area was divided into 13 subplots, according to the distribution of field roads and farmland. An energy consumption model was then constructed in the comprehensive path planning for single plots. The angle of the operation direction depended directly on the operational quality and energy consumption of the tractor. MATLAB platform was used to simulate the comprehensive path planning for the 13 subplots, in order to quantitatively analyze the impact of parameters. The energy consumption costs of the tractor were gradually compared under different operation direction angles in the simulation. The optimal operation direction angle was identified and determined to realize the energy-optimal comprehensive path planning for single plots, together with the optimal entry and exit coordinates for each plot. Finally, the entry and exit positions of each plot were determined to solve the optimal traversal order for the multiple plots using improved whale optimization. The tendency fell into the local optima and premature convergence. Tent mapping was used for the population initialization. The nonlinear convergence factor was introduced to reduce algorithm oscillation and instability. The improved whale optimization balanced the global and local search. The energy-optimal traversal path was successfully planned for the 13 subplots, thus achieving an orderly connection for each subplot. Taking a certain tractor model as the research object, path planning simulation was conducted with energy and path length optimization as the targets. The results showed that the total operation energy consumption was reduced by 22.26%, compared with the optimal scenario of path length. The energy consumption for traversal was 11.71% lower using the improved whale optimization than that using the whale optimization, demonstrating the significant energy-saving. This finding can provide a feasible way for the comprehensive path planning of plots in the hilly and mountainous regions. A theoretical basis was also offered for the global optimization of operation energy.