VISION-BASED VINEYARD TRUNK DETECTION AND ITS INTEGRATION INTO A GRAPES HARVESTING ROBOT – IJMERR, VOL. 10, NO. 7, PP. 374-385, JULY 2021
14 December 2020
GRAPE STEM DETECTION USING REGRESSION CONVOLUTIONAL NEURAL NETWORKS – COMPUTERS AND ELECTRONICS IN AGRICULTURE, VOL. 186, P. 106220, 2021
2 June 2021

AN AUTONOMOUS GRAPE-HARVESTER ROBOT: INTEGRATED SYSTEM ARCHITECTURE – ELECTRONICS, VOL. 10, NO. 9, P. 1056

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.

Citation

E. Vrochidou, K. Tziridis, A. Nikolaou, T. Kalampokas, G. A. Papakostas, T. P. Pachidis, S. Mamalis, S. Koundouras, V G. Kaburlasos, “An autonomous grape-harvester robot: integrated system architecture”, Electronics 2021, 10(9), 1056; https://doi.org/10.3390/electronics10091056 (Special Issue on Control of Mobile Robots – Section “Systems & Control Engineering”. Guest Editor: Vladan Papic).

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