A Petri net based approach for multi-robot path planning
Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal p...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kloetzer, Marius [verfasserIn] Mahulea, Cristian [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Discrete event dynamic systems - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991, 24(2013), 4 vom: 24. März, Seite 417-445 |
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| Übergeordnetes Werk: |
volume:24 ; year:2013 ; number:4 ; day:24 ; month:03 ; pages:417-445 |
| Links: |
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| DOI / URN: |
10.1007/s10626-013-0162-6 |
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| Katalog-ID: |
SPR01195311X |
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| 245 | 1 | 2 | |a A Petri net based approach for multi-robot path planning |
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| 520 | |a Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. | ||
| 650 | 4 | |a Discrete event systems |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Abstractions |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Mobile robots |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Hybrid systems |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Algorithms |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Mahulea, Cristian |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Discrete event dynamic systems |d Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 |g 24(2013), 4 vom: 24. März, Seite 417-445 |w (DE-627)308447379 |w (DE-600)1502222-5 |x 1573-7594 |7 nnns |
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10.1007/s10626-013-0162-6 doi (DE-627)SPR01195311X (SPR)s10626-013-0162-6-e DE-627 ger DE-627 rakwb eng 510 ASE 31.55 bkl 31.00 bkl Kloetzer, Marius verfasserin aut A Petri net based approach for multi-robot path planning 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. Discrete event systems (dpeaa)DE-He213 Abstractions (dpeaa)DE-He213 Mobile robots (dpeaa)DE-He213 Hybrid systems (dpeaa)DE-He213 Algorithms (dpeaa)DE-He213 Mahulea, Cristian verfasserin aut Enthalten in Discrete event dynamic systems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 24(2013), 4 vom: 24. März, Seite 417-445 (DE-627)308447379 (DE-600)1502222-5 1573-7594 nnns volume:24 year:2013 number:4 day:24 month:03 pages:417-445 https://dx.doi.org/10.1007/s10626-013-0162-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.55 ASE 31.00 ASE AR 24 2013 4 24 03 417-445 |
| spelling |
10.1007/s10626-013-0162-6 doi (DE-627)SPR01195311X (SPR)s10626-013-0162-6-e DE-627 ger DE-627 rakwb eng 510 ASE 31.55 bkl 31.00 bkl Kloetzer, Marius verfasserin aut A Petri net based approach for multi-robot path planning 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. Discrete event systems (dpeaa)DE-He213 Abstractions (dpeaa)DE-He213 Mobile robots (dpeaa)DE-He213 Hybrid systems (dpeaa)DE-He213 Algorithms (dpeaa)DE-He213 Mahulea, Cristian verfasserin aut Enthalten in Discrete event dynamic systems Dordrecht [u.a.] : Springer Science + Business Media B.V, 1991 24(2013), 4 vom: 24. März, Seite 417-445 (DE-627)308447379 (DE-600)1502222-5 1573-7594 nnns volume:24 year:2013 number:4 day:24 month:03 pages:417-445 https://dx.doi.org/10.1007/s10626-013-0162-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE 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_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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.55 ASE 31.00 ASE AR 24 2013 4 24 03 417-445 |
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Enthalten in Discrete event dynamic systems 24(2013), 4 vom: 24. März, Seite 417-445 volume:24 year:2013 number:4 day:24 month:03 pages:417-445 |
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Kloetzer, Marius |
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Kloetzer, Marius ddc 510 bkl 31.55 bkl 31.00 misc Discrete event systems misc Abstractions misc Mobile robots misc Hybrid systems misc Algorithms A Petri net based approach for multi-robot path planning |
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510 ASE 31.55 bkl 31.00 bkl A Petri net based approach for multi-robot path planning Discrete event systems (dpeaa)DE-He213 Abstractions (dpeaa)DE-He213 Mobile robots (dpeaa)DE-He213 Hybrid systems (dpeaa)DE-He213 Algorithms (dpeaa)DE-He213 |
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ddc 510 bkl 31.55 bkl 31.00 misc Discrete event systems misc Abstractions misc Mobile robots misc Hybrid systems misc Algorithms |
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ddc 510 bkl 31.55 bkl 31.00 misc Discrete event systems misc Abstractions misc Mobile robots misc Hybrid systems misc Algorithms |
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ddc 510 bkl 31.55 bkl 31.00 misc Discrete event systems misc Abstractions misc Mobile robots misc Hybrid systems misc Algorithms |
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petri net based approach for multi-robot path planning |
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A Petri net based approach for multi-robot path planning |
| abstract |
Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. |
| abstractGer |
Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. |
| abstract_unstemmed |
Abstract This paper presents a procedure for creating a probabilistic finite-state model for mobile robots and for finding a sequence of controllers ensuring the highest probability for reaching some desired regions. The approach starts by using results for controlling affine systems in simpliceal partitions, and then it creates a finite-state representation with history-based probabilities on transitions. This representation is embedded into a Petri Net model with probabilistic costs on transitions, and a highest probability path to reach a set of target regions is found. An online supervising procedure updates the paths whenever a robot deviates from the intended trajectory. The proposed probabilistic framework may prove suitable for controlling mobile robots based on more complex specifications. |
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| title_short |
A Petri net based approach for multi-robot path planning |
| url |
https://dx.doi.org/10.1007/s10626-013-0162-6 |
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| author2 |
Mahulea, Cristian |
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Mahulea, Cristian |
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| doi_str |
10.1007/s10626-013-0162-6 |
| up_date |
2024-07-04T01:08:51.153Z |
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| score |
7.400509 |