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Evgenia Selinger, and Lars Linsen, Efficient Errorbounded Curvature Optimization for Smooth Machining Paths. Journal of Virtual Reality and Broadcasting, 15(2018), no. 2. (urn:nbn:de:0009648202)
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%0 Journal Article %T Efficient Errorbounded Curvature Optimization for Smooth Machining Paths %A Selinger, Evgenia %A Linsen, Lars %J Journal of Virtual Reality and Broadcasting %D 2019 %V 15(2018) %N 2 %@ 18602037 %F selinger2019 %X Automated machining with 3axis robots requires thegeneration of tool paths in form of positions of the tooltip. For 5axis robots, the orientations of the tool ateach position needs to be provided, as well. Such atool path can be described in form of two curves, onefor the positional information (as for 3axis machining)and one for the orientational information, wherethe orientation is given by the vector that points froma point on the orientation curve to the respective pointon the position curve. As the robots need to slow downfor sharp turns, i.e., high curvatures in the tool pathlead to slow processing, our goal is to generate toolpaths with minimized curvatures and a guaranteed errorbound. Starting from an initial tool path, which isgiven in the form of polygonal representations of theposition and orientation curves, we generate optimizedversions of the curves in the form of Bspline curvesthat lie within some error bounds of the input path.Our approach first computes an optimized version ofthe position curve within a tolerance band of the inputcurve. The outcome of this first step can directly beapplied to 3axis machining. Based on this first step,for 5axis machining the orientation curve needs to beupdated to again fit the position curve. Then, the orientationcurve is optimized using a similar approach asfor the position curve, but the error bounds are givenin the form of tolerance frustums that define the tolerancein lead and tilt. For an efficient optimizationprocedure, our approach analyzes the input path andsplits it into small (partially overlapping) groups beforeoptimizing the position curve. The groups are categorizedaccording to their geometric complexity andhandled accordingly using two different optimizationprocedures. The simpler, but faster algorithm uses alocal spline approximation, while the slower, but betteralgorithm uses a local sleeve approach. These algorithmsare adapted to both the position and orientationcurve optimization. Subsequently, the groups arecombined into a complete tool path in the form of G2continuous Bspline curves, where we have one suchcurve for 3axis machining and two such curves definedover the same knot vector for 5axis machining. %L 004 %K 3axis matching %K 5axis matching %K NURBS curves %K g²continuity %K machining %R 10.20385/18602037/15.2018.2 %U http://nbnresolving.de/urn:nbn:de:0009648202 %U http://dx.doi.org/10.20385/18602037/15.2018.2Download
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@Article{selinger2019, author = "Selinger, Evgenia and Linsen, Lars", title = "Efficient Errorbounded Curvature Optimization for Smooth Machining Paths", journal = "Journal of Virtual Reality and Broadcasting", year = "2019", volume = "15(2018)", number = "2", keywords = "3axis matching; 5axis matching; NURBS curves; g{\texttwosuperior}continuity; machining", abstract = "Automated machining with 3axis robots requires thegeneration of tool paths in form of positions of the tooltip. For 5axis robots, the orientations of the tool ateach position needs to be provided, as well. Such atool path can be described in form of two curves, onefor the positional information (as for 3axis machining)and one for the orientational information, wherethe orientation is given by the vector that points froma point on the orientation curve to the respective pointon the position curve. As the robots need to slow downfor sharp turns, i.e., high curvatures in the tool pathlead to slow processing, our goal is to generate toolpaths with minimized curvatures and a guaranteed errorbound. Starting from an initial tool path, which isgiven in the form of polygonal representations of theposition and orientation curves, we generate optimizedversions of the curves in the form of Bspline curvesthat lie within some error bounds of the input path.Our approach first computes an optimized version ofthe position curve within a tolerance band of the inputcurve. The outcome of this first step can directly beapplied to 3axis machining. Based on this first step,for 5axis machining the orientation curve needs to beupdated to again fit the position curve. Then, the orientationcurve is optimized using a similar approach asfor the position curve, but the error bounds are givenin the form of tolerance frustums that define the tolerancein lead and tilt. For an efficient optimizationprocedure, our approach analyzes the input path andsplits it into small (partially overlapping) groups beforeoptimizing the position curve. The groups are categorizedaccording to their geometric complexity andhandled accordingly using two different optimizationprocedures. The simpler, but faster algorithm uses alocal spline approximation, while the slower, but betteralgorithm uses a local sleeve approach. These algorithmsare adapted to both the position and orientationcurve optimization. Subsequently, the groups arecombined into a complete tool path in the form of G2continuous Bspline curves, where we have one suchcurve for 3axis machining and two such curves definedover the same knot vector for 5axis machining.", issn = "18602037", doi = "10.20385/18602037/15.2018.2", url = "http://nbnresolving.de/urn:nbn:de:0009648202" }Download
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TY  JOUR AU  Selinger, Evgenia AU  Linsen, Lars PY  2019 DA  2019// TI  Efficient Errorbounded Curvature Optimization for Smooth Machining Paths JO  Journal of Virtual Reality and Broadcasting VL  15(2018) IS  2 KW  3axis matching KW  5axis matching KW  NURBS curves KW  g²continuity KW  machining AB  Automated machining with 3axis robots requires thegeneration of tool paths in form of positions of the tooltip. For 5axis robots, the orientations of the tool ateach position needs to be provided, as well. Such atool path can be described in form of two curves, onefor the positional information (as for 3axis machining)and one for the orientational information, wherethe orientation is given by the vector that points froma point on the orientation curve to the respective pointon the position curve. As the robots need to slow downfor sharp turns, i.e., high curvatures in the tool pathlead to slow processing, our goal is to generate toolpaths with minimized curvatures and a guaranteed errorbound. Starting from an initial tool path, which isgiven in the form of polygonal representations of theposition and orientation curves, we generate optimizedversions of the curves in the form of Bspline curvesthat lie within some error bounds of the input path.Our approach first computes an optimized version ofthe position curve within a tolerance band of the inputcurve. The outcome of this first step can directly beapplied to 3axis machining. Based on this first step,for 5axis machining the orientation curve needs to beupdated to again fit the position curve. Then, the orientationcurve is optimized using a similar approach asfor the position curve, but the error bounds are givenin the form of tolerance frustums that define the tolerancein lead and tilt. For an efficient optimizationprocedure, our approach analyzes the input path andsplits it into small (partially overlapping) groups beforeoptimizing the position curve. The groups are categorizedaccording to their geometric complexity andhandled accordingly using two different optimizationprocedures. The simpler, but faster algorithm uses alocal spline approximation, while the slower, but betteralgorithm uses a local sleeve approach. These algorithmsare adapted to both the position and orientationcurve optimization. Subsequently, the groups arecombined into a complete tool path in the form of G2continuous Bspline curves, where we have one suchcurve for 3axis machining and two such curves definedover the same knot vector for 5axis machining. SN  18602037 UR  http://nbnresolving.de/urn:nbn:de:0009648202 DO  10.20385/18602037/15.2018.2 ID  selinger2019 ER Download
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<?xml version="1.0" encoding="UTF8"?> <b:Sources SelectedStyle="" xmlns:b="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" > <b:Source> <b:Tag>selinger2019</b:Tag> <b:SourceType>ArticleInAPeriodical</b:SourceType> <b:Year>2019</b:Year> <b:PeriodicalTitle>Journal of Virtual Reality and Broadcasting</b:PeriodicalTitle> <b:Volume>15(2018)</b:Volume> <b:Issue>2</b:Issue> <b:Url>http://nbnresolving.de/urn:nbn:de:0009648202</b:Url> <b:Url>http://dx.doi.org/10.20385/18602037/15.2018.2</b:Url> <b:Author> <b:Author><b:NameList> <b:Person><b:Last>Selinger</b:Last><b:First>Evgenia</b:First></b:Person> <b:Person><b:Last>Linsen</b:Last><b:First>Lars</b:First></b:Person> </b:NameList></b:Author> </b:Author> <b:Title>Efficient Errorbounded Curvature Optimization for Smooth Machining Paths</b:Title> <b:Comments>Automated machining with 3axis robots requires thegeneration of tool paths in form of positions of the tooltip. For 5axis robots, the orientations of the tool ateach position needs to be provided, as well. Such atool path can be described in form of two curves, onefor the positional information (as for 3axis machining)and one for the orientational information, wherethe orientation is given by the vector that points froma point on the orientation curve to the respective pointon the position curve. As the robots need to slow downfor sharp turns, i.e., high curvatures in the tool pathlead to slow processing, our goal is to generate toolpaths with minimized curvatures and a guaranteed errorbound. Starting from an initial tool path, which isgiven in the form of polygonal representations of theposition and orientation curves, we generate optimizedversions of the curves in the form of Bspline curvesthat lie within some error bounds of the input path.Our approach first computes an optimized version ofthe position curve within a tolerance band of the inputcurve. The outcome of this first step can directly beapplied to 3axis machining. Based on this first step,for 5axis machining the orientation curve needs to beupdated to again fit the position curve. Then, the orientationcurve is optimized using a similar approach asfor the position curve, but the error bounds are givenin the form of tolerance frustums that define the tolerancein lead and tilt. For an efficient optimizationprocedure, our approach analyzes the input path andsplits it into small (partially overlapping) groups beforeoptimizing the position curve. The groups are categorizedaccording to their geometric complexity andhandled accordingly using two different optimizationprocedures. The simpler, but faster algorithm uses alocal spline approximation, while the slower, but betteralgorithm uses a local sleeve approach. These algorithmsare adapted to both the position and orientationcurve optimization. Subsequently, the groups arecombined into a complete tool path in the form of G2continuous Bspline curves, where we have one suchcurve for 3axis machining and two such curves definedover the same knot vector for 5axis machining.</b:Comments> </b:Source> </b:Sources>Download
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PT Journal AU Selinger, E Linsen, L TI Efficient Errorbounded Curvature Optimization for Smooth Machining Paths SO Journal of Virtual Reality and Broadcasting PY 2019 VL 15(2018) IS 2 DI 10.20385/18602037/15.2018.2 DE 3axis matching; 5axis matching; NURBS curves; g²continuity; machining AB Automated machining with 3axis robots requires thegeneration of tool paths in form of positions of the tooltip. For 5axis robots, the orientations of the tool ateach position needs to be provided, as well. Such atool path can be described in form of two curves, onefor the positional information (as for 3axis machining)and one for the orientational information, wherethe orientation is given by the vector that points froma point on the orientation curve to the respective pointon the position curve. As the robots need to slow downfor sharp turns, i.e., high curvatures in the tool pathlead to slow processing, our goal is to generate toolpaths with minimized curvatures and a guaranteed errorbound. Starting from an initial tool path, which isgiven in the form of polygonal representations of theposition and orientation curves, we generate optimizedversions of the curves in the form of Bspline curvesthat lie within some error bounds of the input path.Our approach first computes an optimized version ofthe position curve within a tolerance band of the inputcurve. The outcome of this first step can directly beapplied to 3axis machining. Based on this first step,for 5axis machining the orientation curve needs to beupdated to again fit the position curve. Then, the orientationcurve is optimized using a similar approach asfor the position curve, but the error bounds are givenin the form of tolerance frustums that define the tolerancein lead and tilt. For an efficient optimizationprocedure, our approach analyzes the input path andsplits it into small (partially overlapping) groups beforeoptimizing the position curve. The groups are categorizedaccording to their geometric complexity andhandled accordingly using two different optimizationprocedures. The simpler, but faster algorithm uses alocal spline approximation, while the slower, but betteralgorithm uses a local sleeve approach. These algorithmsare adapted to both the position and orientationcurve optimization. Subsequently, the groups arecombined into a complete tool path in the form of G2continuous Bspline curves, where we have one suchcurve for 3axis machining and two such curves definedover the same knot vector for 5axis machining. ERDownload
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<mods> <titleInfo> <title>Efficient Errorbounded Curvature Optimization for Smooth Machining Paths</title> </titleInfo> <name type="personal"> <namePart type="family">Selinger</namePart> <namePart type="given">Evgenia</namePart> </name> <name type="personal"> <namePart type="family">Linsen</namePart> <namePart type="given">Lars</namePart> </name> <abstract>Automated machining with 3axis robots requires the generation of tool paths in form of positions of the tool tip. For 5axis robots, the orientations of the tool at each position needs to be provided, as well. Such a tool path can be described in form of two curves, one for the positional information (as for 3axis machining) and one for the orientational information, where the orientation is given by the vector that points from a point on the orientation curve to the respective point on the position curve. As the robots need to slow down for sharp turns, i.e., high curvatures in the tool path lead to slow processing, our goal is to generate tool paths with minimized curvatures and a guaranteed error bound. Starting from an initial tool path, which is given in the form of polygonal representations of the position and orientation curves, we generate optimized versions of the curves in the form of Bspline curves that lie within some error bounds of the input path. Our approach first computes an optimized version of the position curve within a tolerance band of the input curve. The outcome of this first step can directly be applied to 3axis machining. Based on this first step, for 5axis machining the orientation curve needs to be updated to again fit the position curve. Then, the orientation curve is optimized using a similar approach as for the position curve, but the error bounds are given in the form of tolerance frustums that define the tolerance in lead and tilt. For an efficient optimization procedure, our approach analyzes the input path and splits it into small (partially overlapping) groups before optimizing the position curve. The groups are categorized according to their geometric complexity and handled accordingly using two different optimization procedures. The simpler, but faster algorithm uses a local spline approximation, while the slower, but better algorithm uses a local sleeve approach. These algorithms are adapted to both the position and orientation curve optimization. Subsequently, the groups are combined into a complete tool path in the form of G2 continuous Bspline curves, where we have one such curve for 3axis machining and two such curves defined over the same knot vector for 5axis machining.</abstract> <subject> <topic>3axis matching</topic> <topic>5axis matching</topic> <topic>NURBS curves</topic> <topic>g²continuity</topic> <topic>machining</topic> </subject> <classification authority="ddc">004</classification> <relatedItem type="host"> <genre authority="marcgt">periodical</genre> <genre>academic journal</genre> <titleInfo> <title>Journal of Virtual Reality and Broadcasting</title> </titleInfo> <part> <detail type="volume"> <number>15(2018)</number> </detail> <detail type="issue"> <number>2</number> </detail> <date>2019</date> </part> </relatedItem> <identifier type="issn">18602037</identifier> <identifier type="urn">urn:nbn:de:0009648202</identifier> <identifier type="doi">10.20385/18602037/15.2018.2</identifier> <identifier type="uri">http://nbnresolving.de/urn:nbn:de:0009648202</identifier> <identifier type="citekey">selinger2019</identifier> </mods>Download
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Bibliographic Citation  JVRB, 15(2018), no. 2. 

Title 
Efficient Errorbounded Curvature Optimization for Smooth Machining Paths (eng) 
Author  Evgenia Selinger, Lars Linsen 
Language  eng 
Abstract  Automated machining with 3axis robots requires the generation of tool paths in form of positions of the tool tip. For 5axis robots, the orientations of the tool at each position needs to be provided, as well. Such a tool path can be described in form of two curves, one for the positional information (as for 3axis machining) and one for the orientational information, where the orientation is given by the vector that points from a point on the orientation curve to the respective point on the position curve. As the robots need to slow down for sharp turns, i.e., high curvatures in the tool path lead to slow processing, our goal is to generate tool paths with minimized curvatures and a guaranteed error bound. Starting from an initial tool path, which is given in the form of polygonal representations of the position and orientation curves, we generate optimized versions of the curves in the form of Bspline curves that lie within some error bounds of the input path. Our approach first computes an optimized version of the position curve within a tolerance band of the input curve. The outcome of this first step can directly be applied to 3axis machining. Based on this first step, for 5axis machining the orientation curve needs to be updated to again fit the position curve. Then, the orientation curve is optimized using a similar approach as for the position curve, but the error bounds are given in the form of tolerance frustums that define the tolerance in lead and tilt. For an efficient optimization procedure, our approach analyzes the input path and splits it into small (partially overlapping) groups before optimizing the position curve. The groups are categorized according to their geometric complexity and handled accordingly using two different optimization procedures. The simpler, but faster algorithm uses a local spline approximation, while the slower, but better algorithm uses a local sleeve approach. These algorithms are adapted to both the position and orientation curve optimization. Subsequently, the groups are combined into a complete tool path in the form of G2 continuous Bspline curves, where we have one such curve for 3axis machining and two such curves defined over the same knot vector for 5axis machining. 
Subject  3axis matching, 5axis matching, NURBS curves, g²continuity, machining 
Classified Subjects 

DDC  004 
Rights  DPPL 
URN:  urn:nbn:de:0009648202 
DOI  https://doi.org/10.20385/18602037/15.2018.2 