Conceptual design of an autonomous rover with ground penetrating radar: Application in characterizing soils using deep learning

Abstract

In the pursuit to make agricultural production efficient, the earliest farmers used data in the form of notes of observations. In the current age of data,it has become easier to collect data over a wide spectrum of parameters. There are numerous sensing technologies for measuring processes and parameters over the field surface, typically mounted on satellites, aerial (drone), ground vehicle and static platforms. In the latest understanding, soil is gaining increasing attention and recognition for its significance in not only increasing productivity but also stabilizing the environment. However, characterizing soil in a field is not trivial, especially when required toaccess the deeper layers and quantifying the essential contents –water, nutrients and organic matter. <br/><br/>This paper presents a short review of applications of ground penetrating radars (GPR) in measuring soil content and structure. The focusis ondeeplearning constructs that have been used for interpreting and establishing correlations. The review serves to inform design considerations for a planned autonomous rover that will be used for surveying field soils in the Satakunta region of Finland