Cooperative Grape Harvesting Using Heterogeneous Autonomous Robots

Author:

Lytridis Chris1ORCID,Bazinas Christos1ORCID,Kalathas Ioannis1ORCID,Siavalas George1,Tsakmakis Christos1,Spirantis Theodoros1,Badeka Eftichia1,Pachidis Theodore1ORCID,Kaburlasos Vassilis G.1ORCID

Affiliation:

1. HUMAIN-Lab, International Hellenic University (IHU), 65404 Kavala, Greece

Abstract

The development of agricultural robots is an increasingly popular research field aiming at addressing the widespread labor shortages in the farming industry and the ever-increasing food production demands. In many cases, multiple cooperating robots can be deployed in order to reduce task duration, perform an operation not possible with a single robot, or perform an operation more effectively. Building on previous results, this application paper deals with a cooperation strategy that allows two heterogeneous robots to cooperatively carry out grape harvesting, and its implementation is demonstrated. More specifically, the cooperative grape harvesting task involves two heterogeneous robots, where one robot (i.e., the expert) is assigned the grape harvesting task, whereas the second robot (i.e., the helper) is tasked with supporting the harvesting task by carrying the harvested grapes. The proposed cooperative harvesting methodology ensures safe and effective interactions between the robots. Field experiments have been conducted in order firstly to validate the effectiveness of the coordinated navigation algorithm and secondly to demonstrate the proposed cooperative harvesting method. The paper reports on the conclusions drawn from the field experiments, and recommendations for future enhancements are made. The potential of sophisticated as well as explainable decision-making based on logic for enhancing the cooperation of autonomous robots in agricultural applications is discussed in the context of mathematical lattice theory.

Funder

Technology for Skillful Viniculture

Competitiveness, Entrepreneurship and Innovation

Greece and the European Union

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

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