Intelligent coverage path planning for agricultural robots and autonomous machines on three-dimensional terrain

Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage pattern for a given 2D field has been investigated and reported. However, a great proportion of farms have rolling terrains, which have a considerable influence on the design of coverage paths. Coverage path planning in 3D space has a great potential to further optimize field operations and provide more precise navigation. Supplementary to that, energy consumption models were invoked taking into account terrain inclinations in order to provide the optimal driving direction for traversing the parallel field-work tracks and the optimal sequence for handling these tracks under the criterion of minimizing direct energy requirements. The reduced energy requirements and consequently the reduced emissions of atmospheric pollutants, e.g. CO2 and NO, are of major concern due to their contribution to the greenhouse effect. Based on the results from two case study fields, it was shown that the reduction in the energy requirements when the driving angle is optimized by taking into account the 3D field terrain was 6.5 % as an average for all the examined scenarios compared to the case when the applied driving angle is optimized assuming even field terrain. Additional reduction is achieved when sequence of field tracks is optimized by taking into account inclinations for driving up and down steep hills.