Route planning for orchard operations

Bochtis, Dionysis; Griepentrog, Hans W.; Vougioukas, Stavros; Busato, Patrizia; Berruto, Remigio; Zhou, Kun

doi:10.1016/j.compag.2014.12.024

Cited by 79 publications

(37 citation statements)

References 17 publications

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“…También se detectaron varios autores que se han enfocado en la producción agrícola mecanizada (Baio, et al, 2013;Beaudoin, Frayret y Lebel, 2014;Zhou, et al, 2014;Zhou, et al, 2015;Jensen, Bochtis y Sørensen, 2015;Bochtis, et al, 2015;Edwards, et al, 2015;Montgomery, Han y Kizha, 2016;), que se pueden observar a más detalle en la Tabla 2. Lo dicho hasta aquí supone que, en las actividades agrícolas se está involucrando más fuertemente la maquinaria, esto se puede dar, debido a las optimizaciones que genera el cambio de una operación manual a mecanizada, ya que, en la mayoría de ocasiones, impacta directamente en la reducción de mano de obra y tiempos de operación, que a su vez, genera reducciones en los costos totales de producción.…”

Section: Discusión De Resultadosunclassified

“…Identificar las actividades no productivas en las operaciones de campo que incluyen maquinaria, se descompone el proceso de cobertura de área en acciones de conducción factibles y analizar el potencial de minimizar las actividades no productivas. Bochtis et al (2015) Probar un enfoque de planificación de rutas, utilizando un robot de comportamiento determinístico (denominado AMS -sistema de mecanización autónomo). Esta investigación proporcionará un sistema completo de planificación de rutas para vehículos de huertos autónomos.…”

Section: Pathumnakul Y Nakrachata-amonunclassified

See 1 more Smart Citation

Programación o planeación de actividades o recursos en la agricultura. Una revisión de literatura

Valencia

Aguirre

Herrera

2018

reveia

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Con el propósito de detectar las herramientas y enfoques desarrollados en la programación de recursos o la planeación de actividades en la agricultura, el presente documento muestra la revisión sistemática de literatura adelantada para tal fin, así mismo, expone los resultados y discusión de ellos. Se pretende realizar un diagnóstico del desarrollo de este sector y como está siendo impactado por diferentes herramientas de optimización, que en su mayoría han sido aplicadas en la industria. El documento muestra una introducción general, las ecuaciones de búsqueda utilizadas, las bases de datos en las que fueron aplicadas las ecuaciones de búsqueda, los resultados de la revisión sistemática de literatura y la discusión de los resultados obtenidos.

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Section: Discusión De Resultadosunclassified

Section: Pathumnakul Y Nakrachata-amonunclassified

Programación o planeación de actividades o recursos en la agricultura. Una revisión de literatura

Valencia

Aguirre

Herrera

2018

reveia

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“…The second downside is that the quality of some fruits is not adequately preserved if the bins are not stored promptly . It is therefore desirable to conceive harvesting strategies that prioritize plants according to their expected yield, taking into account the expected time required to complete the harvesting of each plant and also the payload capacity of the truck . As pointed out in Refs.…”

Section: Introductionmentioning

confidence: 99%

Agricultural service unit motion planning under harvesting scheduling and terrain constraints

Cheein

Torres-Torriti

Hopfenblatt

et al. 2017

Journal of Field Robotics

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Most of the existing harvesting strategies rely on traditional path planners that only minimize the length of the path or energy consumption, ignoring the state of the crops and production process. Furthermore, the existing approaches use simplified kinematic models that neglect the robots' dynamics and their interaction with the terrain. To address these limitations, we propose and test in the field a harvesting and motion‐planning strategy that explicitly considers the expected plant yield and the terrain's traversability. The latter has direct impact in the energy management of the agricultural service unit. A map with the predicted yield of each plant is employed to determine a priority queue of harvesting points. The priority queue, together with the harvesting rate and the robot's payload capacity, are used to generate a harvesting schedule for the different locations in the grove. The joint harvesting and motion‐planning strategy applied is evaluated using field data from a Chilean avocado grove during the harvesting season. The results show that the proposed strategy provides a useful approach to automate the harvest points scheduling and motion planning while saving machinery resources.

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“…e " d k´y (8) where d k is the distance between the selected centers for the sample of k. The Gaussian basis function is local to the center vector, in the sense that:…”

Section: Gpx C Imentioning

confidence: 99%

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

et al. 2016

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Abstract:Maize is one of the major food crops in China. Traditionally, field operations are done by manual labor, where the farmers are threatened by the harsh environment and pesticides. On the other hand, it is difficult for large machinery to maneuver in the field due to limited space, particularly in the middle and late growth stage of maize. Unmanned, compact agricultural machines, therefore, are ideal for such field work. This paper describes a method of monocular visual recognition to navigate small vehicles between narrow crop rows. Edge detection and noise elimination were used for image segmentation to extract the stalks in the image. The stalk coordinates define passable boundaries, and a simplified radial basis function (RBF)-based algorithm was adapted for path planning to improve the fault tolerance of stalk coordinate extraction. The average image processing time, including network latency, is 220 ms. The average time consumption for path planning is 30 ms. The fast processing ensures a top speed of 2 m/s for our prototype vehicle. When operating at the normal speed (0.7 m/s), the rate of collision with stalks is under 6.4%. Additional simulations and field tests further proved the feasibility and fault tolerance of our method.

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Route planning for orchard operations

Cited by 79 publications

References 17 publications

Programación o planeación de actividades o recursos en la agricultura. Una revisión de literatura

Programación o planeación de actividades o recursos en la agricultura. Una revisión de literatura

Agricultural service unit motion planning under harvesting scheduling and terrain constraints

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

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