The knowledge of singularity-free regions (SFRs) inside the workspace of a manipulator is helpful in its path-planning and design. To identify such regions analytically, the singularity manifold needs to be determined first. This paper presents the derivation of the gain-type singularity manifold in the task-space of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3$$\end{document}-RPS manipulator, which is further utilised to compute its SFR, in the form of a singularity-free cylinder (SFC), which is free of gain-type singularities. The problem of identifying the longest SFC for a given constant radius and a chosen base circle is posed as a constrained optimisation problem, which reduces to a 21-degree univariate polynomial in the length of the SFC. The formulation is illustrated via a numerical example.


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    Title :

    Analytical Determination of the Longest Cylinder Free of Gain-type Singularities Inside the Workspace of a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3$$\end{document}-RPS Spatial Manipulator


    Additional title:

    Springer Proceedings in Advanced Robotics



    Conference:

    International Symposium on Advances in Robot Kinematics ; 2020 ; Ljubljana, Slovenia December 06, 2020 - December 10, 2020



    Publication date :

    2020-07-18


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English