Revisi\'on de M\'etodos de Planificaci\'on de Camino de Cobertura para Entornos Agr\'icolas

TL;DR

This paper reviews current coverage path planning methods for agricultural robots, detailing two techniques and their combination to improve efficiency in crop coverage tasks, specifically applied to a soybean weeding robot.

Contribution

It provides a comparative analysis of two prevalent coverage planning techniques and discusses their integration for enhanced efficiency in agricultural robot navigation.

Findings

Analysis of obstacle-based cell decomposition method.

Evaluation of strip-based coverage optimization.

Discussion on combining techniques for better global coverage.

Abstract

The use of an efficient coverage planning method is key for autonomous navigation in agricultural environments, where a robot must cover large areas of crops. This paper generally reviews the current state of the art of coverage path planning methods. Two widely used techniques applicable to agricultural environments are described in detail. The first consists of breaking down a complex field with obstacles into simpler subregions known as cells, to subsequently generate a coverage pattern in each of them. The second analyzes spaces composed of parallel strips through which the robot must circulate, in order to find the optimal order of visiting strips that minimizes the total distance traveled. Additionally, the combination of both techniques is discussed in order to obtain a more efficient global coverage plan. This analysis was conceived to be implemented with the soybean crop weeding robot developed at CIFASIS (CONICET-UNR).