Minimising the non-working distance travelled by machines operating in a headland field pattern

Bochtis, Dionysis; Vougioukas, Stavros

doi:10.1016/j.biosystemseng.2008.06.008

Cited by 160 publications

(109 citation statements)

References 6 publications

Supporting

Mentioning

100

Contrasting

Unclassified

Order By: Relevance

“…Ω-turns and Π-turns), which not only reduce the operational cost but also reduce the fatigue of the operator (Holpp et al, 2013) making it possible for the operator to work efficiently for longer periods and at a consistently high level of work quality. Other existing routing methods, such as the B-pattern, introduced by Bochtis & Vougioukas (2008), which computes the optimal track sequence towards minimization of the total non-working turning distance, requires developing a dedicated tool for each agricultural vehicle to implement this type of pattern in each operation. Nevertheless, these standard fieldwork patterns can be directly implemented in the currently available navigationaiding systems (e.g.…”

Section: Discussionmentioning

confidence: 99%

Performance of machinery in potato production in one growing season

Zhou

Jensen

Bochtis

et al. 2015

Span. j. agric. res.

View full text Add to dashboard Cite

Statistics on the machinery performance are essential for farm managers to make better decisions. In this paper, the performance of all machineries in five sequential operations, namely bed forming, stone separation, planting, spraying and harvesting in the potato production system, were investigated during one growing season. In order to analyse and decompose the recorded GPS data into various time and distance elements for estimation of the machinery performance, an automatic GPS analysis tool was developed. The field efficiency and field capacity were estimated for each operation. Specifically, the measured average field efficiency was 71.3% for bed forming, 68.5% for stone separation, 40.3% for planting, 69.7% for spraying, and 67.4% for harvesting. The measured average field capacities were 1.46 ha/h, 0.53 ha/h, 0.47 ha/h, 10.21 ha/h, 0.51 ha/h, for the bed forming, stone separation, planting, spraying, and harvesting operations, respectively. These results deviate from the corresponding estimations calculated based on norm data from the American Society of Agricultural and Biological Engineers (ASABE). The deviations indicate that norms provided by ASABE cannot be used directly for the prediction of performance of the machinery used in this work. Moreover, the measured data of bed forming and stone separation could be used as supplementary data for the ASABE which does not provide performance norms for these two operations. The gained results can help farm managers to make better management and operational decisions that result in potential improvement in productivity and profitability as well as in potential environmental benefits.Additional key words: GPS data analysis; operation management; machinery management; field efficiency; field capacity; Solanum tuberosum L.

show abstract

Section: Discussionmentioning

confidence: 99%

Performance of machinery in potato production in one growing season

Zhou

Jensen

Bochtis

et al. 2015

Span. j. agric. res.

View full text Add to dashboard Cite

show abstract

“…In an attempt to increase crop performance (i.e., crop yield) on poor patches, farm managers or contractors may apply additional inputs by modern machines (Oliver et al, 2010). But its implementation is subject to the crop rows and the location of sparsely located patches, thus the pattern of field operation affects very much the time lost in the field due to the non-working travel stems from the turning at headlands (Taylor et al, 2002;Palmer et al, 2003;Bochtis & Vougioukas, 2008), as well as the nonproductive transition inside the field interior. Therefore, an optimal fieldwork pattern is essential to improve the efficiency of such operations.…”

Section: Introductionmentioning

confidence: 99%

Improving the efficiency of spatially selective operations for agricultural robotics in cropping field

2013

Span. j. agric. res.

View full text Add to dashboard Cite

Cropping fields often have well-defined poor-performing patches due to spatial and temporal variability. In an attempt to increase crop performance on poor patches, spatially selective field operations may be performed by agricultural robotics to apply additional inputs with targeted requirements. This paper addresses the route planning problem for an agricultural robot that has to treat some poor-patches in a field with row crops, with respect to the minimization of the total non-working distance travelled during headland turnings and in-field travel distance. The traversal of patches in the field is expressed as the traversal of a mixed weighted graph, and then the problem of finding an optimal patch sequence is formulated as an asymmetric traveling salesman problem and solved by the parthenogenetic algorithm. The proposed method is applied on a cropping field located in Northwestern China. Research results show that by using optimum patch sequences, the total non-working distance travelled during headland turnings and in-field travel distance can be reduced. But the savings on the non-working distance inside the field interior depend on the size and location of patches in the field, and the introduction of agricultural robotics is beneficial to increase field efficiency.Additional key words: ASTP; autonomous machines; field operations; fieldwork pattern; patch spraying; precision agriculture; spatially selective application. * Corresponding author: lyl_mac@126.com Received: 01-07-12. Accepted: 31-01-13.Abbreviations used: ATSP (asymmetric traveling salesman problem); AU (application unit); GIS (geographical information system); GPS (global positioning system); RS (remote sensing); RU (refilling unit).

show abstract

“…Th e analyses of the machinery movement, optimal direction of movement, algorithms and mathematical models of machinery fi eld traffi c were conducted by Bochtis et al (2007Bochtis et al ( , 2010a, Oksanen and Visala (2007), Bochtis and Vougioukas (2008), Yakusshev and Yakusshev (2008), Spekken and Bruin (2011) and others.…”

mentioning

confidence: 99%

Determining the guidance system accuracy with the support of a large GNSS dataset

Rataj¹,

Galambošová²,

Vašek³

2013

Res. Agric. Eng.

View full text Add to dashboard Cite

Rataj V., Galambošová J., Vašek M., 2013. Determining the guidance system accuracy with the support of a large GNSS dataset. Res. Agr. Eng., 59 (Special Issue): S65-S70.Several methods are used presently to assess the accuracy of machinery guidance systems. However, these off er a limited number of records and are time and cost consuming. As the machinery is often equipped with a monitoring system for the management purposes, these data can be used. Th e aim of this work was to develop and verify a method to determine the accuracy of the machinery guidance systems based on a large dataset obtained from the machinery monitoring system. Th e proposed method uses the transformation of global navigation satellite systems (GNSS) data into a rectangular coordinate system SJTSK (National projection system -Krovak projection). Based on the geometry principle, the ideal line can be determined, and afterwards, the off -track error of each actual position can be calculated. After the verifi cation of this method, it can be concluded that it brings benefi ts in terms of further use of the data from the monitoring systems, the estimation of the error based on a robust dataset, elimination of subjective and measurement method errors, as well as spatial localisation of the off -track errors at the fi eld.Keywords: off -track error; geometry; rectangular coordinate system SJTSK Th e machinery movement in the fi eld is an important parameter of the machinery use effi ciency. Th e research into this topic has been conducted for many years by many authors from many aspects. Among the fi rst published results on the fi eld traffi c are those by Pavlov et al. (1973) and Ondej et al. (1989). Th e problem of the machinery movement is connected with the technical level of tractors and implements. Because of the kinematics of modern tractors, it is necessary nowadays to study and model the machinery movement. Several authors deal with the aspects of machinery movement itself including the kinematics (Backman et al. 2012;Rovira-Más 2012). Th e issue of the machinery movement within a defi ned space, described by the shape and the area of a fi eld, has been solved by Hameed et al. (2010). Besides the movement of machinery for the fi eld operations, those of machinery for service operations such as e.g. fi eld transport have been analysed (Bochtis et al. 2010a).Th e analyses of the machinery movement, optimal direction of movement, algorithms and mathematical models of machinery fi eld traffi c were conducted by Bochtis et al. (2007Bochtis et al. ( , 2010a, Oksanen and Visala (2007), Bochtis and Vougioukas (2008), Yakusshev and Yakusshev (2008), Spekken and Bruin (2011) and others.

show abstract

Minimising the non-working distance travelled by machines operating in a headland field pattern

Cited by 160 publications

References 6 publications

Performance of machinery in potato production in one growing season

Performance of machinery in potato production in one growing season

Improving the efficiency of spatially selective operations for agricultural robotics in cropping field

Determining the guidance system accuracy with the support of a large GNSS dataset

Contact Info

Product

Resources

About