Robotic data collection platform with artificial vision applied to precision agriculture

Abstract

Precision agriculture currently requires increasingly robust and integrated technological supports to search and analyze the data it uses. On the other hand, the different types of sensors that currently exist provide information banks that in many cases, remain disconnected from the context in which they are obtain. This paper proposes a model of data collection in the field based on the use of a robotic autonomous navigation platform with tours inside or outside of trials. Its objective is to sense by artificial vision the different phenological stages of a crop throughout its development, integrate, process and inform them. This model is based on the use of RGB cameras and spectral cameras connected to a tracking system, digital signal processing techniques, and stereoscopic and geo-positioning navigation techniques.