Multi-Objective Seed Curve Optimization for Coverage Path Planning in Precision Farming.

Coverage path planning is one of the main challenges in precision farming. Here the goal is to compute a continuous optimal working path by combining individual tracks such that the entire field can be cultivated in the most efficient way. Various 2D and 3D approaches have already been presented in the literature. However, these are lacking in two major aspects: In each case, a seed curve is determined and offsetted to generate the individual tracks, but the seed curve is usually selected from a predefined set of alternatives. Additionally, the utilized objectives do not consider the efficiency of the tools used to work on the field, which typically depends on the path angle and the field's inclination. In this paper, we propose a scheme to cope with both aspects through an evolutionary multiobjective optimization approach. Three objectives are used, namely coverage, energy based on anisotropic friction and gravity, and precession, which describes the angle between the path direction and the gradient of the terrain.