Wang, Q.; Zhang, Q.; Rovira Más, F.; Tian, L. (2011). Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields. Biosystems Engineering. 109:258-265. doi:10.1016/j.biosystemseng.2011.04.006
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/63178
Título:
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Stereovision-based lateral offset measurement for vehicle navigation in cultivated stubble fields
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Autor:
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Wang, Qi
Zhang, Qin
Rovira Más, Francisco
Tian, Lei
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària
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Fecha difusión:
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Resumen:
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In auto-guidance of agricultural vehicles in cultivated stubble fields, a precise measurement of the vehicle's lateral offset could help achieve improved navigation accuracy. This paper presents an automated method for ...[+]
In auto-guidance of agricultural vehicles in cultivated stubble fields, a precise measurement of the vehicle's lateral offset could help achieve improved navigation accuracy. This paper presents an automated method for measuring a vehicle's lateral offset for such an application. The basic concept was to use static ground features as references to detect the vehicle's lateral offset. A stereo image-processing algorithm was developed which detected and tracked ground features captured in two consecutive field images, acquired using a vehicle-mounted stereo camera. These ground features were used as reference points to calculate the lateral offset. Field validation tests showed that this algorithm could provide accurate relative lateral offset measurements. Over a 10 m straight path, the deviation of measurements from ground truth was less than 50 mm. As this method was designed to measure relative offset, the field tests also revealed that it needed a realignment of the installation pose of the camera and the desired heading direction of the vehicle after a turn to ensure the measurement deviation less than 50 mm. Although the realignment algorithm was outside the scope of this research, the results proved the possibility of using an imaging sensor for the detection of the lateral offset of a vehicle to guide agricultural vehicles automatically in cultivated stubble fields without obvious referencing landmarks. © 2011 IAgrE.
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Palabras clave:
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Agricultural vehicles
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Auto guidances
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Automated methods
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Basic concepts
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Consecutive fields
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Field test
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Field validation
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Ground truth
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Image-processing algorithms
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Imaging sensors
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Measurement deviations
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Navigation accuracy
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Precise measurements
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Reference points
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Stereo cameras
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Vehicle navigation
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Algorithms
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Cameras
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Navigation
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Vehicles
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Derechos de uso:
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Cerrado |
Fuente:
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Biosystems Engineering. (issn:
1537-5110
) (eissn:
1537-5129
)
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DOI:
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10.1016/j.biosystemseng.2011.04.006
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Editorial:
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Elsevier
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Versión del editor:
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http://dx.doi.org/10.1016/j.biosystemseng.2011.04.006
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Código del Proyecto:
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info:eu-repo/grantAgreement/NIFA//WNP0728/US
info:eu-repo/grantAgreement/NIFA//WNP0745/US
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Agradecimientos:
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This research was supported in part by Washington State University Agricultural Research Center federal formula funds, Project No. WNP0745 and No. WNP0728 received from the U.S. Department of Agriculture National Institutes ...[+]
This research was supported in part by Washington State University Agricultural Research Center federal formula funds, Project No. WNP0745 and No. WNP0728 received from the U.S. Department of Agriculture National Institutes for Food and Agriculture (NIFA) and by Bruce Cowgur Mid-Tech Memorial Funds. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author and do not necessarily reflect the view of the U.S. Department of Agriculture, Washington State University, the University of Illinois, the Polytechnic University of Valencia, or Midwest Technologies, Inc.
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Tipo:
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Artículo
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