The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints
Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Manor, Gil [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: |
© Springer Science+Business Media New York 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Autonomous robots - Springer US, 1994, 41(2016), 2 vom: 12. Feb., Seite 385-400 |
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| Übergeordnetes Werk: |
volume:41 ; year:2016 ; number:2 ; day:12 ; month:02 ; pages:385-400 |
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| DOI / URN: |
10.1007/s10514-015-9538-9 |
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| 520 | |a Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. | ||
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10.1007/s10514-015-9538-9 doi (DE-627)OLC205275069X (DE-He213)s10514-015-9538-9-p DE-627 ger DE-627 rakwb eng 620 VZ Manor, Gil verfasserin aut The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. Mobile robot time optimal navigation High speed navigation Mobile robot safety Rimon, Elon aut Enthalten in Autonomous robots Springer US, 1994 41(2016), 2 vom: 12. Feb., Seite 385-400 (DE-627)186689446 (DE-600)1252189-9 (DE-576)053002199 0929-5593 nnns volume:41 year:2016 number:2 day:12 month:02 pages:385-400 https://doi.org/10.1007/s10514-015-9538-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 41 2016 2 12 02 385-400 |
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10.1007/s10514-015-9538-9 doi (DE-627)OLC205275069X (DE-He213)s10514-015-9538-9-p DE-627 ger DE-627 rakwb eng 620 VZ Manor, Gil verfasserin aut The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. Mobile robot time optimal navigation High speed navigation Mobile robot safety Rimon, Elon aut Enthalten in Autonomous robots Springer US, 1994 41(2016), 2 vom: 12. Feb., Seite 385-400 (DE-627)186689446 (DE-600)1252189-9 (DE-576)053002199 0929-5593 nnns volume:41 year:2016 number:2 day:12 month:02 pages:385-400 https://doi.org/10.1007/s10514-015-9538-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 41 2016 2 12 02 385-400 |
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10.1007/s10514-015-9538-9 doi (DE-627)OLC205275069X (DE-He213)s10514-015-9538-9-p DE-627 ger DE-627 rakwb eng 620 VZ Manor, Gil verfasserin aut The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. Mobile robot time optimal navigation High speed navigation Mobile robot safety Rimon, Elon aut Enthalten in Autonomous robots Springer US, 1994 41(2016), 2 vom: 12. Feb., Seite 385-400 (DE-627)186689446 (DE-600)1252189-9 (DE-576)053002199 0929-5593 nnns volume:41 year:2016 number:2 day:12 month:02 pages:385-400 https://doi.org/10.1007/s10514-015-9538-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 41 2016 2 12 02 385-400 |
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10.1007/s10514-015-9538-9 doi (DE-627)OLC205275069X (DE-He213)s10514-015-9538-9-p DE-627 ger DE-627 rakwb eng 620 VZ Manor, Gil verfasserin aut The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. Mobile robot time optimal navigation High speed navigation Mobile robot safety Rimon, Elon aut Enthalten in Autonomous robots Springer US, 1994 41(2016), 2 vom: 12. Feb., Seite 385-400 (DE-627)186689446 (DE-600)1252189-9 (DE-576)053002199 0929-5593 nnns volume:41 year:2016 number:2 day:12 month:02 pages:385-400 https://doi.org/10.1007/s10514-015-9538-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 AR 41 2016 2 12 02 385-400 |
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Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. © Springer Science+Business Media New York 2016 |
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Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. © Springer Science+Business Media New York 2016 |
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Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure. © Springer Science+Business Media New York 2016 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC205275069X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502215343.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10514-015-9538-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC205275069X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10514-015-9538-9-p</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="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Manor, Gil</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints</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">© Springer Science+Business Media New York 2016</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper considers the synthesis of pseudo time optimal paths for a mobile robot navigating among obstacles subject to uniform braking safety constraints. The classical Brachistochrone problem studies the time optimal path of a particle moving in an obstacle free environment subject to a constant force field. By encoding the mobile robot’s braking safety constraint as a force field surrounding each obstacle, the paper generalizes the Brachistochrone problem into safe time optimal navigation of a mobile robot in environments populated by polygonal obstacles. Convexity of the safe travel time functional, a path dependent function, allows efficient construction of a speed graph for the environment. The speed graph consists of safe time optimal arcs computed as convex optimization problems in $$O(n^3 \log (1/\epsilon ))$$ total time, where n is the number of obstacle features in the environment and $$\epsilon $$ is the desired solution accuracy. Once the speed graph is constructed for a given environment, pseudo time optimal paths between any start and target robot positions can be computed along the speed graph in $$O(n^2\log n)$$ time. The results are illustrated with examples and described as a readily implementable procedure.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mobile robot time optimal navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">High speed navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mobile robot safety</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rimon, Elon</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Autonomous robots</subfield><subfield code="d">Springer US, 1994</subfield><subfield code="g">41(2016), 2 vom: 12. 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