In this section
@article{Cursi:2022:10.1109/ACCESS.2022.3141660,
author = {Cursi, F and Bai, W and Yeatman, EM and Kormushev, P},
doi = {10.1109/ACCESS.2022.3141660},
journal = {IEEE Access},
pages = {5012--5023},
title = {GlobDesOpt: a global optimization framework for optimal robot manipulator design},
url = {http://dx.doi.org/10.1109/ACCESS.2022.3141660},
volume = {10},
year = {2022}
}
TY - JOUR
AB - 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.
AU - Cursi,F
AU - Bai,W
AU - Yeatman,EM
AU - Kormushev,P
DO - 10.1109/ACCESS.2022.3141660
EP - 5023
PY - 2022///
SN - 2169-3536
SP - 5012
TI - GlobDesOpt: a global optimization framework for optimal robot manipulator design
T2 - IEEE Access
UR - http://dx.doi.org/10.1109/ACCESS.2022.3141660
UR - https://ieeexplore.ieee.org/abstract/document/9674897
UR - http://hdl.handle.net/10044/1/93772
VL - 10
ER -
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