GlobDesOpt: A Global Optimization Framework for Optimal Robot Manipulator Design

被引:6
作者
Cursi, Francesco [1 ,2 ]
Bai, Weibang [1 ]
Yeatman, Eric M. [1 ]
Kormushev, Petar [2 ]
机构
[1] Imperial Coll London, Hamlyn Ctr, London SW7 2BX, England
[2] Imperial Coll London, Robot Intelligence Lab, London SW7 2BX, England
基金
英国工程与自然科学研究理事会;
关键词
Robots; Optimization; Manipulators; Genetic algorithms; Task analysis; Ellipsoids; Cost function; Robot design; Global optimization; Robot kinematics;
D O I
10.1109/ACCESS.2022.3141660
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Robot design is a major component in robotics, as it allows building robots capable of performing properly in given tasks. However, designing a robot with multiple types of parameters and constraints and defining an optimization function analytically for the robot design problem may be intractable or even impossible. Therefore black-box optimization approaches are generally preferred. In this work we propose GlobDesOpt, a simple-to-use open-source optimization framework for robot design based on global optimization methods. The framework allows selecting various design parameters and optimizing for both single and dual-arm robots. The functionalities of the framework are shown here to optimally design a dual-arm surgical robot, comparing the different two optimization strategies.
引用
收藏
页码:5012 / 5023
页数:12
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