title: Active optical sensors for tree stem detection and classification in nurseries.
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.
authors.affiliation: Laboratorio de Propiedades Físicas (LPF)-TAGRALIA, Technical University of Madrid, Madrid 28040, Spain. miguel.garrido.izard@upm.es.
authors.forename: Miguel
authors.initials: M
authors.lastname: Garrido
authors.affiliation: Aerospace Engineering and Fluids Mechanics Department, University of Seville, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain. manuelperez@us.es.
authors.forename: Manuel
authors.initials: M
authors.lastname: Perez-Ruiz
authors.affiliation: Laboratorio de Propiedades Físicas (LPF)-TAGRALIA, Technical University of Madrid, Madrid 28040, Spain. constantino.valero@upm.es.
authors.forename: Constantino
authors.initials: C
authors.lastname: Valero
authors.affiliation: Department of Plant Sciences and Biological and Agricultural Engineering, Sensor and Instrumentation Lab, University of California, Davis, One Shields Ave, Davis, CA 95616, USA. cjgliever@ucdavis.edu.
authors.forename: Chris J
authors.initials: CJ
authors.lastname: Gliever
authors.affiliation: Department of Plant Sciences and Biological and Agricultural Engineering, Sensor and Instrumentation Lab, University of California, Davis, One Shields Ave, Davis, CA 95616, USA. bhanson@ucdavis.edu.
authors.forename: Bradley D
authors.initials: BD
authors.lastname: Hanson
authors.affiliation: Department of Plant Sciences and Biological and Agricultural Engineering, Sensor and Instrumentation Lab, University of California, Davis, One Shields Ave, Davis, CA 95616, USA. dcslaughter@ucdavis.edu.
authors.forename: David C
authors.initials: DC
authors.lastname: Slaughter
mesh_terms: D000383:Agriculture / Q000295:instrumentation* / Q000379:methods*; D000465:Algorithms; D004867:Equipment Design; D019544:Equipment Failure Analysis; D007834:Lasers; D010363:Pattern Recognition, Automated / Q000379:methods*; D018547:Plant Stems / Q000033:anatomy & histology / Q000145:classification* / Q000502:physiology; D036226:Seedlings / Q000033:anatomy & histology / Q000145:classification* / Q000502:physiology; D014159:Transducers; D014197:Trees / Q000033:anatomy & histology / Q000145:classification* / Q000502:physiology