Occupancy grid mapping with the use of a forward sonar model by gradient descent
Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shvets, E. A. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Anmerkung: |
© Pleiades Publishing, Inc. 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of communications technology and electronics - Pleiades Publishing, 1993, 61(2016), 12 vom: Dez., Seite 1474-1480 |
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| Übergeordnetes Werk: |
volume:61 ; year:2016 ; number:12 ; month:12 ; pages:1474-1480 |
| Links: |
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| DOI / URN: |
10.1134/S106422691612024X |
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OLC2059687365 |
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| 520 | |a Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). | ||
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| 700 | 1 | |a Nikolaev, D. P. |4 aut | |
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10.1134/S106422691612024X doi (DE-627)OLC2059687365 (DE-He213)S106422691612024X-p DE-627 ger DE-627 rakwb eng 620 VZ Shvets, E. A. verfasserin aut Occupancy grid mapping with the use of a forward sonar model by gradient descent 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Inc. 2016 Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). sonar-based mapping occupancy maps forward sonar model continuous optimization Shepelev, D. A. aut Nikolaev, D. P. aut Enthalten in Journal of communications technology and electronics Pleiades Publishing, 1993 61(2016), 12 vom: Dez., Seite 1474-1480 (DE-627)171168402 (DE-600)1160383-5 (DE-576)038494272 1064-2269 nnns volume:61 year:2016 number:12 month:12 pages:1474-1480 https://doi.org/10.1134/S106422691612024X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 61 2016 12 12 1474-1480 |
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10.1134/S106422691612024X doi (DE-627)OLC2059687365 (DE-He213)S106422691612024X-p DE-627 ger DE-627 rakwb eng 620 VZ Shvets, E. A. verfasserin aut Occupancy grid mapping with the use of a forward sonar model by gradient descent 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Inc. 2016 Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). sonar-based mapping occupancy maps forward sonar model continuous optimization Shepelev, D. A. aut Nikolaev, D. P. aut Enthalten in Journal of communications technology and electronics Pleiades Publishing, 1993 61(2016), 12 vom: Dez., Seite 1474-1480 (DE-627)171168402 (DE-600)1160383-5 (DE-576)038494272 1064-2269 nnns volume:61 year:2016 number:12 month:12 pages:1474-1480 https://doi.org/10.1134/S106422691612024X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 61 2016 12 12 1474-1480 |
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10.1134/S106422691612024X doi (DE-627)OLC2059687365 (DE-He213)S106422691612024X-p DE-627 ger DE-627 rakwb eng 620 VZ Shvets, E. A. verfasserin aut Occupancy grid mapping with the use of a forward sonar model by gradient descent 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Inc. 2016 Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). sonar-based mapping occupancy maps forward sonar model continuous optimization Shepelev, D. A. aut Nikolaev, D. P. aut Enthalten in Journal of communications technology and electronics Pleiades Publishing, 1993 61(2016), 12 vom: Dez., Seite 1474-1480 (DE-627)171168402 (DE-600)1160383-5 (DE-576)038494272 1064-2269 nnns volume:61 year:2016 number:12 month:12 pages:1474-1480 https://doi.org/10.1134/S106422691612024X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 61 2016 12 12 1474-1480 |
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Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). © Pleiades Publishing, Inc. 2016 |
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Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). © Pleiades Publishing, Inc. 2016 |
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Abstract Mapping of the environment is one of the key functions of autonomous robots. An efficient mapping algorithm is needed for successful localization and path finding. Maps may be plotted on the basis of the data from various sensors. Cheap and easy-to-install sonars are typically used for this purpose. A sonar-based mapping algorithm based on continuous optimization methods is proposed. This algorithm may be used in real time, and its main advantages over the common methods are more accurate determination of the size of small (smaller than the sonar beam width or comparable to it) obstacles and more reliable detection of narrow passages (e.g., doorways). © Pleiades Publishing, Inc. 2016 |
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A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Occupancy grid mapping with the use of a forward sonar model by gradient descent</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Pleiades Publishing, Inc. 2016</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Mapping of the environment is one of the key functions of autonomous robots. 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