Optimal design of assembling robot considering different limb topologies and layouts

Binbin Lian, Jinhua Guo, Zhiyuan He, Yimin Song
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Abstract

A class of 5 degree-of-freedom (DoF) hybrid robots consisting of one translational and two rotational (1T2R) parallel module and 2T serial module is presented for assembling in the aircraft cabin. The 1T2R parallel modules are with three limb topologies (PRS, RRS and internal closed-loop) and two layouts (symmetrical and “T” shape). Herein, P, R and S denote prismatic, rotational and spherical joints. This paper presents the multi-objective optimization of the hybrid robot regarding different limb topology, limb layout and corresponding dimensions as design variables. Considering demands from the in-cabin assembling, kinematic, linear stiffness along z-axis and total mass of the robot are the objectives. The Pareto fronts and cooperative equilibrium point (CEP) indicate that the robot with 3-PRS and 3-RRS parallel module have better performances than the one with internal closed-loop. The overall performances of robot with symmetrical layout are superior than the one with “T” shape layout. In addition, two optimization methods are compared. One is to separately optimize six robots with specific topology and layout. The other is to optimize all design variables in a model. It is found that six robots have their own performance zones. Therefore, final optimums of two methods are close to each other. But optimization in one model is able to eliminate unfeasible topologies in the early stage of searching and thus is more efficient. Optimal module is 3-PRS with symmetrical layout. Experiments on the physical prototype validates performances of the optimal robot.
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考虑不同肢体拓扑结构和布局的装配机器人优化设计
本文介绍了一种由一个平移和两个旋转(1T2R)并联模块和 2T 串行模块组成的 5 自由度(DoF)混合机器人,用于在飞机机舱内进行组装。1T2R 并行模块有三种肢体拓扑结构(PRS、RRS 和内部闭环)和两种布局(对称和 "T "形)。其中,P、R 和 S 分别表示棱柱关节、旋转关节和球形关节。本文以不同的肢体拓扑结构、肢体布局和相应的尺寸为设计变量,对混合机器人进行了多目标优化。考虑到舱内装配的需求,机器人的运动学、沿 Z 轴的线性刚度和总质量是优化目标。帕累托前沿和合作平衡点(CEP)表明,采用 3-PRS 和 3-RRS 并联模块的机器人比采用内部闭环的机器人性能更好。对称布局机器人的总体性能优于 "T "形布局机器人。此外,还比较了两种优化方法。一种是分别优化六种具有特定拓扑结构和布局的机器人。另一种是在一个模型中优化所有设计变量。结果发现,六个机器人有各自的性能区。因此,两种方法的最终最优值相互接近。但在一个模型中进行优化能够在搜索的早期阶段消除不可行的拓扑结构,因此效率更高。最佳模块是对称布局的 3-PRS 模块。在物理原型上进行的实验验证了最优机器人的性能。
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