Robotic Grasping of Harvested Tomato Trusses Using Vision and Online Learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F24%3A00375256" target="_blank" >RIV/68407700:21730/24:00375256 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/ICRA57147.2024.10610089" target="_blank" >https://doi.org/10.1109/ICRA57147.2024.10610089</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICRA57147.2024.10610089" target="_blank" >10.1109/ICRA57147.2024.10610089</a>

Result language

angličtina

Original language name

Robotic Grasping of Harvested Tomato Trusses Using Vision and Online Learning

Original language description

Currently, truss tomato weighing and packaging require significant manual work. The main obstacle to automation lies in the difficulty of developing a reliable robotic grasping system for already harvested trusses. We propose a method to grasp trusses that are stacked in a crate with considerable clutter, which is how they are commonly stored and transported after harvest. The method consists of a deep learning-based vision system to first identify the individual trusses in the crate and then determine a suitable grasping location on the stem. To this end, we have introduced a grasp pose ranking algorithm with online learning capabilities. After selecting the most promising grasp pose, the robot executes a pinch grasp without needing touch sensors or geometric models. Lab experiments with a robotic manipulator equipped with an eye-in-hand RGB-D camera showed a 100% clearance rate when tasked to pick all trusses from a pile. 93% of the trusses were successfully grasped on the first try, while the remaining 7% required more attempts.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2024 IEEE International Conference on Robotics and Automation (ICRA)

ISBN

979-8-3503-8457-4

ISSN

1050-4729

e-ISSN

2577-087X

Number of pages

7

Pages from-to

13947-13953

Publisher name

IEEE Industrial Electronic Society

Place of publication

Vienna

Event location

Yokohama

Event date

May 13, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001369728003111