Screw theory is a powerful mathematical tool for the kinematic analysis of mechanisms and has become a cornerstone of modern kinematics. Although screw theory has rooted itself as a core concept, there is a lack of generic software tools for visualization of the geometric pattern of the screw elements. This paper presents STORM, an educational and research oriented framework for analysis and visualization of reciprocal screw systems for a class of robot manipulator and mechanisms. This platform has been developed as a way to bridge the gap between theory and practice of application of screw theory in the constraint and motion analysis for robot mechanisms. STORM utilizes an abstracted software architecture that enables the user to study different structures of robot manipulators. The example case studies demonstrate the potential to perform analysis on mechanisms, visualize the screw entities and conveniently add new models and analyses.

STORM: Screw theory toolbox for robot manipulator and mechanisms

Keerthi Sagar Somenedi Rao.;Ramadoss V.;Zlatanov D.;Zoppi M.
2020-01-01

Abstract

Screw theory is a powerful mathematical tool for the kinematic analysis of mechanisms and has become a cornerstone of modern kinematics. Although screw theory has rooted itself as a core concept, there is a lack of generic software tools for visualization of the geometric pattern of the screw elements. This paper presents STORM, an educational and research oriented framework for analysis and visualization of reciprocal screw systems for a class of robot manipulator and mechanisms. This platform has been developed as a way to bridge the gap between theory and practice of application of screw theory in the constraint and motion analysis for robot mechanisms. STORM utilizes an abstracted software architecture that enables the user to study different structures of robot manipulators. The example case studies demonstrate the potential to perform analysis on mechanisms, visualize the screw entities and conveniently add new models and analyses.
2020
978-1-7281-6212-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1047816
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