GlobDesOpt: a global optimization framework for optimal robot manipulator design
File(s)
Author(s)
Cursi, Francesco
Bai, Weibang
Yeatman, Eric M
Kormushev, Petar
Type
Journal Article
Abstract
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.
Date Issued
2022-02-01
Date Acceptance
2022-01-06
Citation
IEEE Access, 2022, 10, pp.5012-5023
ISSN
2169-3536
Publisher
IEEE
Start Page
5012
End Page
5023
Journal / Book Title
IEEE Access
Volume
10
Copyright Statement
© 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
License URL
Identifier
https://ieeexplore.ieee.org/abstract/document/9674897
Subjects
08 Information and Computing Sciences
09 Engineering
10 Technology
Publication Status
Published
Date Publish Online
2022-01-07