{"title":"Symbolic and User-friendly Geometric Algebra Routines (SUGAR) for Computations in Matlab","authors":"Manel Velasco, Isiah Zaplana, Arnau Dória-Cerezo, Pau Martí","doi":"arxiv-2403.16634","DOIUrl":null,"url":null,"abstract":"Geometric algebra (GA) is a mathematical tool for geometric computing,\nproviding a framework that allows a unified and compact approach to geometric\nrelations which in other mathematical systems are typically described using\ndifferent more complicated elements. This fact has led to an increasing\nadoption of GA in applied mathematics and engineering problems. However, the\nscarcity of symbolic implementations of GA and its inherent complexity,\nrequiring a specific mathematical background, make it challenging and less\nintuitive for engineers to work with. This prevents wider adoption among more\napplied professionals. To address this challenge, this paper introduces SUGAR\n(Symbolic and User-friendly Geometric Algebra Routines), an open-source toolbox\ndesigned for Matlab and licensed under the MIT License. SUGAR facilitates the\ntranslation of GA concepts into Matlab and provides a collection of\nuser-friendly functions tailored for GA computations, including support for\nsymbolic operations. It supports both numeric and symbolic computations in\nhigh-dimensional GAs. Specifically tailored for applied mathematics and\nengineering applications, SUGAR has been meticulously engineered to represent\ngeometric elements and transformations within two and three-dimensional\nprojective and conformal geometric algebras, aligning with established\ncomputational methodologies in the literature. Furthermore, SUGAR efficiently\nhandles functions of multivectors, such as exponential, logarithmic,\nsinusoidal, and cosine functions, enhancing its applicability across various\nengineering domains, including robotics, control systems, and power\nelectronics. Finally, this work includes four distinct validation examples,\ndemonstrating SUGAR's capabilities across the above-mentioned fields and its\npractical utility in addressing real-world applied mathematics and engineering\nproblems.","PeriodicalId":501062,"journal":{"name":"arXiv - CS - Systems and Control","volume":"119 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2403.16634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Geometric algebra (GA) is a mathematical tool for geometric computing,
providing a framework that allows a unified and compact approach to geometric
relations which in other mathematical systems are typically described using
different more complicated elements. This fact has led to an increasing
adoption of GA in applied mathematics and engineering problems. However, the
scarcity of symbolic implementations of GA and its inherent complexity,
requiring a specific mathematical background, make it challenging and less
intuitive for engineers to work with. This prevents wider adoption among more
applied professionals. To address this challenge, this paper introduces SUGAR
(Symbolic and User-friendly Geometric Algebra Routines), an open-source toolbox
designed for Matlab and licensed under the MIT License. SUGAR facilitates the
translation of GA concepts into Matlab and provides a collection of
user-friendly functions tailored for GA computations, including support for
symbolic operations. It supports both numeric and symbolic computations in
high-dimensional GAs. Specifically tailored for applied mathematics and
engineering applications, SUGAR has been meticulously engineered to represent
geometric elements and transformations within two and three-dimensional
projective and conformal geometric algebras, aligning with established
computational methodologies in the literature. Furthermore, SUGAR efficiently
handles functions of multivectors, such as exponential, logarithmic,
sinusoidal, and cosine functions, enhancing its applicability across various
engineering domains, including robotics, control systems, and power
electronics. Finally, this work includes four distinct validation examples,
demonstrating SUGAR's capabilities across the above-mentioned fields and its
practical utility in addressing real-world applied mathematics and engineering
problems.