# Optimal In-field Routing for Full and Partial Field Coverage with Arbitrary Non-Convex Fields and Multiple Obstacle Areas

## TL;DR

This paper presents two algorithms for optimal in-field routing in agriculture, capable of handling complex non-convex fields and obstacles, improving efficiency for full and partial coverage tasks.

## Contribution

It introduces novel algorithms for full and partial field coverage routing in complex fields with obstacles, tailored for precision agriculture and logistical efficiency.

## Key findings

- Algorithms tested on real-world fields show high efficiency.
- Effective handling of non-convex fields and obstacles.
- Suitable for both full and partial coverage tasks.

## Abstract

Within the context of optimising the logistics in agriculture this paper relates to optimal in-field routing for full and partial field coverage with arbitrary non-convex fields and multiple obstacle areas. It is distinguished between nine different in-field routing tasks: two for full-field coverage, seven for partial-field coverage and one for shortest path planning between any two vertices of the transition graph. It differentiates between equal or different start and end vertices for a task, coverage of only a subset of vertices, and a subset of edges or combinations. The proposed methods are developed primarily for applying sprays and fertilisers with larger operating widths and with fields where there is unique headland path. Partial field coverage where, e.g., only a specific subset of edges has to be covered is relevant for precision agriculture and also for optimised logistical operation of smaller-sized machinery with limited loading capacities. The result of this research is the proposition of two compatible algorithms for optimal full and partial field coverage path planning, respectively. These are evaluated on three real-world fields to demonstrate their characteristics and computational efficiency.