Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.

Garrido Izard, Miguel and Pérez Ruiz, Manuel and Valero Ubierna, Constantino and Gliever, Chris J. and Hanson, Bradley D. and Slaughter, David (2014). Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.. "Sensors", v. 14 (n. 6); pp. 10783-10803. ISSN 1424-8220. https://doi.org/10.3390/s140610783.

Description

Title: Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.
Author/s:
  • Garrido Izard, Miguel
  • Pérez Ruiz, Manuel
  • Valero Ubierna, Constantino
  • Gliever, Chris J.
  • Hanson, Bradley D.
  • Slaughter, David
Item Type: Article
Título de Revista/Publicación: Sensors
Date: June 2014
ISSN: 1424-8220
Volume: 14
Subjects:
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Ingeniería Rural [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7245986RHEAUnspecifiedROBOT FLEETS FOR HIGHLY EFFECTIVE AGRICULTURE AND FORESTRY MANAGEMENT

More information

Item ID: 30207
DC Identifier: http://oa.upm.es/30207/
OAI Identifier: oai:oa.upm.es:30207
DOI: 10.3390/s140610783
Official URL: http://www.mdpi.com/1424-8220/14/6/10783
Deposited by: Memoria Investigacion
Deposited on: 24 Jun 2014 15:32
Last Modified: 11 Apr 2019 10:39
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