An Autonomous Grape-Harvester Robot: Integrated System Architecture

Abstract

This work pursues the potential of extending “Industry 4.0” practices to farming toward achieving “Agriculture 4.0”. Our interest is in fruit harvesting, motivated by the problem of addressing the shortage of seasonal labor. In particular, here we present an integrated system architecture of an Autonomous Robot for Grape harvesting (ARG). The overall system consists of three interdependent units: (1) an aerial unit, (2) a remote-control unit and (3) the ARG ground unit. Special attention is paid to the ARG; the latter is designed and built to carry out three viticultural operations, namely harvest, green harvest and defoliation. We present an overview of the multi-purpose overall system, the specific design of each unit of the system and the integration of all subsystems. In addition, the fully sensory-based sensing system architecture and the underlying vision system are analyzed. Due to its modular design, the proposed system can be extended to a variety of different crops and/or orchards.

Task Space Model Predictive Control for Vineyard Spraying with a Mobile Manipulator

“…Research efforts have already been directed towards the development of robots for vineyard-related tasks [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. The same applies to robots in agricultural spraying tasks [2,[6][7][8][9]11,13,23].…”

“…In [21], Bouloumpasi et al discuss the possibilities and limitations of autonomous robot technology for performing different tasks in viticulture. Vrochnidou et al [22] present the system architecture of an autonomous robot for grape harvesting, and discuss the vision system used for the task of grape harvesting.…”

A Non-Destructive Method for Grape Ripeness Estimation Using Intervals’ Numbers (INs) Techniques

“…Moreover, the method is designated for in-field real-time maturity assessment by an autonomous harvesting robot; the latter implies that realistic scenarios must be tested, so images with varying illumination need to be used. The camera was mounted on a robotic arm of an autonomous harvester robot [27]. The camera captured the images facing the grape clusters vertically at a fixed distance from the vine tree so as to ensure consistency in the result-at a distance of about 50 cm from the grape cluster and a height of about 70 cm from the ground.…”

Machine Vision for Ripeness Estimation in Viticulture Automation

“…Only the green channel of RGB color space is investigated, small image dataset acquired from video frames. Able for monitoring and harvesting, already integrated in an agrobot [60].…”