Optimization of Workspace Partitioning using Weighted Voronoi Diagram for Fleet of Autonomous Tractors

The automation of agricultural systems is essential for enhancing productivity and ensuring sustainable food production. The introduction of autonomous tractors and fleet of autonomous tractors technology is important to the advancement of agricultural automation. This paper proposes an optimization method for workspace partitioning using a weighted voronoi diagram for fleet of autonomous tractors. The proposed method generates a node map based on an orchard environment, determines the centers of the areas to partition the workspace to be assigned to the k tractors, sets weights based on the specifications of each tractor, optimizes these weights, and partition the workspace to maximize work efficiency.This study validated the performance of workspace partitioning optimization through simulations and field evaluations. The results of this study expect that the proposed method can be applied to fleet of autonomous tractors technology to improve the efficiency of agricultural work.