Computer Vision-Based Guidance Assistance Concept for Plowing Using RGB-D Camera

TL;DR

This paper introduces a computer vision system using RGB-D cameras to assist agricultural vehicle guidance during plowing, aiming to improve accuracy and reduce driver workload and energy consumption.

Contribution

It presents a novel furrow detection system based on RGB-D camera technology for guiding agricultural vehicles during plowing operations.

Findings

Developed a furrow detection algorithm using RGB-D data.

Potential to increase plowing accuracy and reduce fuel consumption.

Enhances driver assistance in agricultural machinery.

Abstract

This paper proposes a concept of computer vision-based guidance assistance for agricultural vehicles to increase the accuracy in plowing and reduce driver's cognitive burden in long-lasting tillage operations. Plowing is a common agricultural practice to prepare the soil for planting in many countries and it can take place both in the spring and the fall. Since plowing operation requires high traction forces, it causes increased energy consumption. Moreover, longer operation time due to unnecessary maneuvers leads to higher fuel consumption. To provide necessary information for the driver and the control unit of the tractor, a first concept of furrow detection system based on an RGB-D camera was developed.