Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking
Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jeon, Chan-Woo [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Precision agriculture - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999, 25(2023), 1 vom: 18. Aug., Seite 235-256 |
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| Übergeordnetes Werk: |
volume:25 ; year:2023 ; number:1 ; day:18 ; month:08 ; pages:235-256 |
| Links: |
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| DOI / URN: |
10.1007/s11119-023-10066-0 |
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| Katalog-ID: |
SPR054336406 |
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| 520 | |a Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). | ||
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10.1007/s11119-023-10066-0 doi (DE-627)SPR054336406 (SPR)s11119-023-10066-0-e DE-627 ger DE-627 rakwb eng Jeon, Chan-Woo verfasserin aut Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 Kim, Hak-Jin aut Yun, Changho aut Park, Seung-Jin aut Hwang, Ye Been aut Han, Xiongzhe aut Enthalten in Precision agriculture Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999 25(2023), 1 vom: 18. Aug., Seite 235-256 (DE-627)320569551 (DE-600)2016333-2 1573-1618 nnns volume:25 year:2023 number:1 day:18 month:08 pages:235-256 https://dx.doi.org/10.1007/s11119-023-10066-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 25 2023 1 18 08 235-256 |
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10.1007/s11119-023-10066-0 doi (DE-627)SPR054336406 (SPR)s11119-023-10066-0-e DE-627 ger DE-627 rakwb eng Jeon, Chan-Woo verfasserin aut Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 Kim, Hak-Jin aut Yun, Changho aut Park, Seung-Jin aut Hwang, Ye Been aut Han, Xiongzhe aut Enthalten in Precision agriculture Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999 25(2023), 1 vom: 18. Aug., Seite 235-256 (DE-627)320569551 (DE-600)2016333-2 1573-1618 nnns volume:25 year:2023 number:1 day:18 month:08 pages:235-256 https://dx.doi.org/10.1007/s11119-023-10066-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 25 2023 1 18 08 235-256 |
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10.1007/s11119-023-10066-0 doi (DE-627)SPR054336406 (SPR)s11119-023-10066-0-e DE-627 ger DE-627 rakwb eng Jeon, Chan-Woo verfasserin aut Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 Kim, Hak-Jin aut Yun, Changho aut Park, Seung-Jin aut Hwang, Ye Been aut Han, Xiongzhe aut Enthalten in Precision agriculture Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999 25(2023), 1 vom: 18. Aug., Seite 235-256 (DE-627)320569551 (DE-600)2016333-2 1573-1618 nnns volume:25 year:2023 number:1 day:18 month:08 pages:235-256 https://dx.doi.org/10.1007/s11119-023-10066-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 25 2023 1 18 08 235-256 |
| allfieldsGer |
10.1007/s11119-023-10066-0 doi (DE-627)SPR054336406 (SPR)s11119-023-10066-0-e DE-627 ger DE-627 rakwb eng Jeon, Chan-Woo verfasserin aut Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 Kim, Hak-Jin aut Yun, Changho aut Park, Seung-Jin aut Hwang, Ye Been aut Han, Xiongzhe aut Enthalten in Precision agriculture Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999 25(2023), 1 vom: 18. Aug., Seite 235-256 (DE-627)320569551 (DE-600)2016333-2 1573-1618 nnns volume:25 year:2023 number:1 day:18 month:08 pages:235-256 https://dx.doi.org/10.1007/s11119-023-10066-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 25 2023 1 18 08 235-256 |
| allfieldsSound |
10.1007/s11119-023-10066-0 doi (DE-627)SPR054336406 (SPR)s11119-023-10066-0-e DE-627 ger DE-627 rakwb eng Jeon, Chan-Woo verfasserin aut Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 Kim, Hak-Jin aut Yun, Changho aut Park, Seung-Jin aut Hwang, Ye Been aut Han, Xiongzhe aut Enthalten in Precision agriculture Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999 25(2023), 1 vom: 18. Aug., Seite 235-256 (DE-627)320569551 (DE-600)2016333-2 1573-1618 nnns volume:25 year:2023 number:1 day:18 month:08 pages:235-256 https://dx.doi.org/10.1007/s11119-023-10066-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 25 2023 1 18 08 235-256 |
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Enthalten in Precision agriculture 25(2023), 1 vom: 18. Aug., Seite 235-256 volume:25 year:2023 number:1 day:18 month:08 pages:235-256 |
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Enthalten in Precision agriculture 25(2023), 1 vom: 18. Aug., Seite 235-256 volume:25 year:2023 number:1 day:18 month:08 pages:235-256 |
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Jeon, Chan-Woo @@aut@@ Kim, Hak-Jin @@aut@@ Yun, Changho @@aut@@ Park, Seung-Jin @@aut@@ Hwang, Ye Been @@aut@@ Han, Xiongzhe @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR054336406</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240111064643.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240111s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11119-023-10066-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR054336406</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11119-023-10066-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jeon, Chan-Woo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual).</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Path planning</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Puddling and leveling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Paddy field</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Autonomous tractor</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kim, Hak-Jin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yun, Changho</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Park, Seung-Jin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hwang, Ye Been</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Han, Xiongzhe</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Precision agriculture</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media B.V, 1999</subfield><subfield code="g">25(2023), 1 vom: 18. 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|
| author |
Jeon, Chan-Woo |
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Jeon, Chan-Woo misc Path planning misc Puddling and leveling misc Paddy field misc Autonomous tractor Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
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Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking Path planning (dpeaa)DE-He213 Puddling and leveling (dpeaa)DE-He213 Paddy field (dpeaa)DE-He213 Autonomous tractor (dpeaa)DE-He213 |
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misc Path planning misc Puddling and leveling misc Paddy field misc Autonomous tractor |
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misc Path planning misc Puddling and leveling misc Paddy field misc Autonomous tractor |
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misc Path planning misc Puddling and leveling misc Paddy field misc Autonomous tractor |
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Elektronische Aufsätze Aufsätze Elektronische Ressource |
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Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
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Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
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Jeon, Chan-Woo |
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Precision agriculture |
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Jeon, Chan-Woo Kim, Hak-Jin Yun, Changho Park, Seung-Jin Hwang, Ye Been Han, Xiongzhe |
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Jeon, Chan-Woo |
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10.1007/s11119-023-10066-0 |
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autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
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Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
| abstract |
Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract In planning the path for a puddling and leveling tractor in a paddy field, achieving multiple leveling across the whole area with minimal traversal while synchronously utilizing a rotary cultivator and a paddy-drive harrow is a key design requirement. This study describes the development of an autonomous puddling and leveling tractor equipped with an optimal coverage path planner (CPP) designed to enable the tractor to level the entire field more than twice using the paddy-drive harrow with foldable wings after prior tilling by the rotary cultivator in fields with irregular shapes. The genetic algorithm was employed to determine the optimal sequence of inner tracks by minimizing the headland turning distance and traversal throughout the field. The feasibility of the developed planner was investigated through simulation studies involving three different shapes of paddy fields, followed by a field test comparing autonomous and manually driven tractors. The simulation results confirmed that the developed CPP effectively achieved the proposed implement strategy and significantly improved efficiency by reducing headland turning distances by 28.5% (pentagon), 33.9% (trapezoid) and 45.0% (rectangle) compared to those obtained from the CPP with gathering track pattern used in a previous study. In the field test, the autonomous tractor demonstrated superior performance in distance and fuel efficiency over the manually operated tractor with comparable leveling capability. Although the operation time was increased by 30.3% because of the lower speed during headland turning, the autonomous tractor reduced travel distance and fuel consumption by 36.1% and 4.7%, respectively, reducing multiple or non-worked areas while resulting in similar altitude variability of 0.24 m (autonomous) compared to 0.19 m (manual). © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Autonomous paddy field puddling and leveling operations based on full-coverage path generation and tracking |
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https://dx.doi.org/10.1007/s11119-023-10066-0 |
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Kim, Hak-Jin Yun, Changho Park, Seung-Jin Hwang, Ye Been Han, Xiongzhe |
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Kim, Hak-Jin Yun, Changho Park, Seung-Jin Hwang, Ye Been Han, Xiongzhe |
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10.1007/s11119-023-10066-0 |
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2024-07-04T01:07:31.689Z |
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|
| score |
7.40114 |