A mission planner for an autonomous tractor

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Standard

A mission planner for an autonomous tractor. / Bochtis, Dionysis; Vougioukas, S.G.; Griepentrog, Hans W.

I: Transactions of the ASAE, Bind 52, Nr. 5, 2009, s. 1429-1440.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Bochtis, D, Vougioukas, SG & Griepentrog, HW 2009, 'A mission planner for an autonomous tractor', Transactions of the ASAE, bind 52, nr. 5, s. 1429-1440.

APA

Bochtis, D., Vougioukas, S. G., & Griepentrog, H. W. (2009). A mission planner for an autonomous tractor. Transactions of the ASAE, 52(5), 1429-1440.

Vancouver

Bochtis D, Vougioukas SG, Griepentrog HW. A mission planner for an autonomous tractor. Transactions of the ASAE. 2009;52(5):1429-1440.

Author

Bochtis, Dionysis ; Vougioukas, S.G. ; Griepentrog, Hans W. / A mission planner for an autonomous tractor. I: Transactions of the ASAE. 2009 ; Bind 52, Nr. 5. s. 1429-1440.

Bibtex

@article{d7ec4080d42011dea1f3000ea68e967b,
title = "A mission planner for an autonomous tractor",
abstract = "In this article, a mission planner of field coverage operations for an autonomous agricultural tractor is presented. Missions for a particular autonomous tractor are defined using an XML (extendible markup language) formatted file that can be uploaded to the tractor through the user interface. Using the tree hierarchy of the mission file, several actions are determined, including the sequence of points the tractor has to follow, the type of motion between successive points (e.g.,straight motion or maneuvering), the type of predefined turning routine used in maneuvering, and the actions that should be taken once the tractor reaches the desired point (e.g., raising or lowering the attached tool, turning on or turning off the ower take-off). In order to automatically create the XML mission files, a program was developed using the MATLAB technical programming language. The program uses data regarding the field (geometry, dimensions, field sub-regions, working direction, initial and final desired locations of the tractor), the operating width, and the operation type (mowing, spraying) as inputs. The planning method is based on an algorithmic approach where field coverage planning is transformed and formulated, via semantic representations, as a vehicle routing problem (VRP). By using this approach, the total non-working distance can be reduced by up to 50{\%} compared to the conventional non-optimized method. Three sets of experiments are presented. In the first set, three fields were separately covered; in the second set, three neighboring fields were covered as part of a single tractor mission; and in the third set of experiments, a single field was covered during a hypothetical spraying operation for two different locations of the refilling facility.",
keywords = "BRIC, Agricultural robots, Automatic, Machinery management, Optimization models, Planning",
author = "Dionysis Bochtis and S.G. Vougioukas and Griepentrog, {Hans W.}",
year = "2009",
language = "English",
volume = "52",
pages = "1429--1440",
journal = "American Society of Agricultural and Biological Engineers. Transactions",
issn = "2151-0032",
publisher = "American Society of Agricultural and Biological Engineers",
number = "5",

}

RIS

TY - JOUR

T1 - A mission planner for an autonomous tractor

AU - Bochtis, Dionysis

AU - Vougioukas, S.G.

AU - Griepentrog, Hans W.

PY - 2009

Y1 - 2009

N2 - In this article, a mission planner of field coverage operations for an autonomous agricultural tractor is presented. Missions for a particular autonomous tractor are defined using an XML (extendible markup language) formatted file that can be uploaded to the tractor through the user interface. Using the tree hierarchy of the mission file, several actions are determined, including the sequence of points the tractor has to follow, the type of motion between successive points (e.g.,straight motion or maneuvering), the type of predefined turning routine used in maneuvering, and the actions that should be taken once the tractor reaches the desired point (e.g., raising or lowering the attached tool, turning on or turning off the ower take-off). In order to automatically create the XML mission files, a program was developed using the MATLAB technical programming language. The program uses data regarding the field (geometry, dimensions, field sub-regions, working direction, initial and final desired locations of the tractor), the operating width, and the operation type (mowing, spraying) as inputs. The planning method is based on an algorithmic approach where field coverage planning is transformed and formulated, via semantic representations, as a vehicle routing problem (VRP). By using this approach, the total non-working distance can be reduced by up to 50% compared to the conventional non-optimized method. Three sets of experiments are presented. In the first set, three fields were separately covered; in the second set, three neighboring fields were covered as part of a single tractor mission; and in the third set of experiments, a single field was covered during a hypothetical spraying operation for two different locations of the refilling facility.

AB - In this article, a mission planner of field coverage operations for an autonomous agricultural tractor is presented. Missions for a particular autonomous tractor are defined using an XML (extendible markup language) formatted file that can be uploaded to the tractor through the user interface. Using the tree hierarchy of the mission file, several actions are determined, including the sequence of points the tractor has to follow, the type of motion between successive points (e.g.,straight motion or maneuvering), the type of predefined turning routine used in maneuvering, and the actions that should be taken once the tractor reaches the desired point (e.g., raising or lowering the attached tool, turning on or turning off the ower take-off). In order to automatically create the XML mission files, a program was developed using the MATLAB technical programming language. The program uses data regarding the field (geometry, dimensions, field sub-regions, working direction, initial and final desired locations of the tractor), the operating width, and the operation type (mowing, spraying) as inputs. The planning method is based on an algorithmic approach where field coverage planning is transformed and formulated, via semantic representations, as a vehicle routing problem (VRP). By using this approach, the total non-working distance can be reduced by up to 50% compared to the conventional non-optimized method. Three sets of experiments are presented. In the first set, three fields were separately covered; in the second set, three neighboring fields were covered as part of a single tractor mission; and in the third set of experiments, a single field was covered during a hypothetical spraying operation for two different locations of the refilling facility.

KW - BRIC

KW - Agricultural robots

KW - Automatic

KW - Machinery management

KW - Optimization models

KW - Planning

M3 - Journal article

VL - 52

SP - 1429

EP - 1440

JO - American Society of Agricultural and Biological Engineers. Transactions

JF - American Society of Agricultural and Biological Engineers. Transactions

SN - 2151-0032

IS - 5

ER -

ID: 15892628