Dynamic modeling and Multi-Objective Optimization of a 3DOF Reconfigurable Parallel Robot

IF 0.6 4区 工程技术 Q4 MECHANICS Mechanics of Solids Pub Date : 2024-11-01 DOI:10.1134/S0025654424603483
M. R. Salehi Kolahi, H. Moeinkhah, H. Rahmani, A. Mohammadzadeh
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Abstract

The reconfigurable parallel robots are highly adaptable to different tasks and environments, making them suitable for a wide range of industrial and medical applications. Optimizing the geometrical and structural parameters is a crucial aspect of designing a parallel robot. However, due to different degrees of freedom and workspaces, the optimization of reconfigurable parallel robots is a challenge. This paper presents the design, unified dynamic modeling and multi-objective optimization methodology of an innovative 3UPS-PU/S robot. This parallel robot can be reconfigured from a Tricept mechanism into a fully spherical mechanism through the reconfiguration of the PU/S central passive limb. For this purpose, the unified dynamic model of the robot is derived. With respect to workspace, manipulability and dynamic dexterity, three performance indices are considered as the objective functions. The robot is optimized with respect to the design and geometrical constraints using the non-dominated sorting genetic algorithm II (NSGA-II), which is used to find the Pareto fronts. The obtained solutions are a set of optimal geometric parameters to adjust the kinematic and dynamic performances. The results depict that the process effectively identified a 3UPS-PU/S robot with an efficient dexterous workspace. Also, based on the optimization results a prototype of the robot was fabricated. Overall, this paper provides a novel framework for the multi-objective optimization of reconfigurable parallel robots.

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3DOF 可重构并行机器人的动态建模和多目标优化
可重构并联机器人对不同任务和环境具有很强的适应性,因此适合广泛的工业和医疗应用。优化几何和结构参数是设计并联机器人的一个重要方面。然而,由于自由度和工作空间的不同,可重构并联机器人的优化是一项挑战。本文介绍了创新型 3UPS-PU/S 机器人的设计、统一动态建模和多目标优化方法。通过重新配置 PU/S 中心被动肢体,该并联机器人可从 Tricept 机构重新配置为全球形机构。为此,推导出了机器人的统一动态模型。在工作空间、可操作性和动态灵巧性方面,考虑了三个性能指标作为目标函数。使用非支配排序遗传算法 II(NSGA-II)对机器人的设计和几何约束进行优化,该算法用于寻找帕累托前沿。所获得的解决方案是一组调整运动学和动力学性能的最优几何参数。结果表明,该过程有效地确定了具有高效灵巧工作空间的 3UPS-PU/S 机器人。此外,还根据优化结果制作了机器人原型。总之,本文为可重构并行机器人的多目标优化提供了一个新框架。
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来源期刊
Mechanics of Solids
Mechanics of Solids 医学-力学
CiteScore
1.20
自引率
42.90%
发文量
112
审稿时长
6-12 weeks
期刊介绍: Mechanics of Solids publishes articles in the general areas of dynamics of particles and rigid bodies and the mechanics of deformable solids. The journal has a goal of being a comprehensive record of up-to-the-minute research results. The journal coverage is vibration of discrete and continuous systems; stability and optimization of mechanical systems; automatic control theory; dynamics of multiple body systems; elasticity, viscoelasticity and plasticity; mechanics of composite materials; theory of structures and structural stability; wave propagation and impact of solids; fracture mechanics; micromechanics of solids; mechanics of granular and geological materials; structure-fluid interaction; mechanical behavior of materials; gyroscopes and navigation systems; and nanomechanics. Most of the articles in the journal are theoretical and analytical. They present a blend of basic mechanics theory with analysis of contemporary technological problems.
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