Introduction of A Row-Skip Pattern in Complete Coverage Path Planning for Agricultural Fields

Over the past two decades, an evolutionary effort has been established in the agricultural sector to develop efficient autonomous systems that can carry out common in-field operations including harvesting, mowing, and spraying. Increasing production while decreasing costs and environmental damages is one of the main objectives for these autonomous systems. Due to the nature of these tasks, complete coverage path planning techniques are crucial to determining the best path that covers the entire field while accounting for terrain characteristics, operational needs, and robot properties. In this study, we propose a novel complete coverage path planning approach to define the ideal path for a wheeled robot across an agricultural field. To identify all feasible solutions satisfying a set of predefined constraints, a method based on tree exploration is first proposed that examines row-skip patterns. Second, the most optimal solution is selected by a selection method. Maximizing the covered area while minimizing overlaps, non-working path length, number of turns containing reverse moves, and overall travel time are the objectives of the selection method. We showed on 6 real-world fields geometries that the row skip approach offered benefits in terms of reduction of the required headland size, and often helped decreasing the number of necessary reverse moves and the overlaps, while increasing the covered area.