3D-Vision Based Detection, Localisation and Sizing of Broccoli Heads in the Field

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00311498" target="_blank" >RIV/68407700:21230/17:00311498 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1002/rob.21726" target="_blank" >http://dx.doi.org/10.1002/rob.21726</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/rob.21726" target="_blank" >10.1002/rob.21726</a>

Result language

angličtina

Original language name

3D-Vision Based Detection, Localisation and Sizing of Broccoli Heads in the Field

Original language description

This paper describes a 3D vision system for robotic harvesting of broccoli using low-cost RGB-D sensors, which was developed and evaluated using sensory data collected under real-world field conditions in both the UK and Spain. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machine learning and temporal filtering methods for detection of broccoli heads. Our experiments show that a combination of Viewpoint Feature Histograms, Support Vector Machine classifier and a temporal filter to track the detected heads results in a system that detects broccoli heads with high precision. We also show that the temporal filtering can be used to generate a 3D map of the broccoli head positions in the field. Additionally we present methods for automatically estimating the size of the broccoli heads, to determine when a head is ready for harvest. All of the methods were evaluated using ground-truth data from both the UK and Spain, which we also make available to the research community for subsequent algorithm development and result comparison. Cross-validation of the system trained on the UK dataset on the Spanish dataset, and vice versa, indicated good generalisation capabilities of the system, confirming the strong potential of low-cost 3D imaging for commercial broccoli harvesting.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

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/GJ17-27006Y" target="_blank" >GJ17-27006Y: Spatio-temporal representations for life-long mobile robot navigation</a><br>

Continuities

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

Publication year

2017

Confidentiality

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

Name of the periodical

Journal of Field Robotics

ISSN

1556-4959

e-ISSN

1556-4967

Volume of the periodical

34

Issue of the periodical within the volume

8

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

1505-1518

UT code for WoS article

000414680500007

EID of the result in the Scopus database

2-s2.0-85020072313