The determination of kinematic parameters for a parallel robotic system (PRS) is an important and a critical phase to maximize reachable workspace while avoiding singular configurations. Stewart Platform (SP) mechanism is one of the widely known PRS and it is used to demonstrate the proposed technique. In the related literature, GCI (Global Condition Index) and LCI (Local Condition Index) are the commonly used performance indexes which give a measure about the dexterity of a mechanism. In this work, Sequential Quadratic Programming (SQP) method is used to optimize kinematic parameters of a 6dof 3x3 UPU SP in order to reach maximum workspace satisfying small condition numbers. The radius of mobile and base platforms and the lengths of the legs used in the platform are chosen as kinematic parameters to be optimized in a multiobjective optimization problem. Optimization is performed at different stages and the number of optimized kinematic parameters is increased at each level. In conclusion, optimizing selected kinematic parameters at once by using SQP technique presents the best results for the PRS.
This article describes a sophisticated determination and presentation of a workspace volume for a delta robot, with consideration of its kinematic behavior. With the help of theoretical equations, optimization is performed with the aid of the stiffness and dexterity analysis. Theoretical substructure is coded in Matlab and three-dimensional (3D) data for delta robot are developed in computer-aided design (CAD) environment. In later stages of the project, both 3D and theoretical data are linked together and thus, with the changing design parameter of the robot itself, the Solidworks CAD output adapts and regenerates output with a new set of parameters. To achieve an optimum workspace volume with predefined parameters, a different set of robot parameters are iterated through design optimization in Matlab, and the delta robot design is finalized and illustrated in the 3D CAD environment, Solidworks. This study provides a technical solution to accomplish a generic delta robot with optimized workspace volume.UDC Classification: 62-1/-9 DOI: http://dx
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.