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Extremal Point Tracking on Smooth Surfaces

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Abstract

Kinematic and dynamic simulations of colliding and sliding bodies have traditionally been based on triangulated object representations, which lead to numerical inaccuracies due to wrong surface normals and inaccurate surface representations. Moreover, contact layers are needed to be able to do efficient simulations. For simulating tight fitting assembly operations, this is particularly critical as the size of numerical inaccuracies and the contact layer are similar to the size of the slack during insertion. Simulations using mathematical surface representations such as planes, cylinders, ellipsoids and B-splines are becoming increasingly popular, and are not suffering from these flaws. It is typically more expensive to find contact points, but once they are found, the contact points can be tracked efficiently if the extrema is unique (singularity free). In this paper, we extend this tracking method for efficiently handling, and also tracking in (near)-singular situations. We outline how this can be done and illustrate it on two cases with singularities.

Original languageEnglish
Title of host publication2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)
PublisherIEEE
Publication date2022
Pages1144-1150
ISBN (Electronic)9781665490429
DOIs
Publication statusPublished - 2022
Event18th IEEE International Conference on Automation Science and Engineering, CASE 2022 - Mexico City, Mexico
Duration: 20. Aug 202224. Aug 2022

Conference

Conference18th IEEE International Conference on Automation Science and Engineering, CASE 2022
Country/TerritoryMexico
CityMexico City
Period20/08/202224/08/2022
SeriesProceedings - IEEE International Conference on Automation Science and Engineering
Volume2022-August
ISSN2161-8070

Funding

1Steffen Madsen and Milad Jami are with Robotics Lab, Device Manufacturing Development, Novo Nordisk A/S, Brennum Park 24K DK-3400 Hillerød, Denmark [email protected]; [email protected] 2Henrik G. Petersen is with the Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55 DK-5230 Odense M, Denmark [email protected] *Steffen Madsen wishes to thank Innovation Fund Denmark for their financial support

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