Integrated optimal design and control of variable stiffness actuated robots

Altay Zhakatayev; Matteo Rubagotti; H. Atakan Varol

doi:10.1109/ECC.2015.7330687

Integrated optimal design and control of variable stiffness actuated robots

Altay Zhakatayev, Matteo Rubagotti, H. Atakan Varol

Department of Robotics and Mechatronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper proposes a method to determine the optimal value of design parameters in robots driven by variable-stiffness actuators. The method consists of setting up a nonlinear optimization problem, the solution of which determines the optimal control sequence, and, at the same time, the optimal values of the parameters. As a case study, we analyze a ball-throwing problem for a two-link elbow manipulator actuated by antagonistic quadratic springs, and show results for different configurations. Even if similar methods have already been proposed, mainly in process control, this approach is novel when applied to robots, and could lead to an overall improvement of their design, exploiting numerical optimization tools, which, in the last years, have become faster and more reliable.

Original language	English
Title of host publication	2015 European Control Conference, ECC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1100-1105
Number of pages	6
ISBN (Print)	9783952426937
DOIs	https://doi.org/10.1109/ECC.2015.7330687
Publication status	Published - Nov 16 2015
Event	European Control Conference, ECC 2015 - Linz, Austria Duration: Jul 15 2015 → Jul 17 2015

Other

Other	European Control Conference, ECC 2015
Country	Austria
City	Linz
Period	7/15/15 → 7/17/15

ASJC Scopus subject areas

Control and Systems Engineering

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abstract = "This paper proposes a method to determine the optimal value of design parameters in robots driven by variable-stiffness actuators. The method consists of setting up a nonlinear optimization problem, the solution of which determines the optimal control sequence, and, at the same time, the optimal values of the parameters. As a case study, we analyze a ball-throwing problem for a two-link elbow manipulator actuated by antagonistic quadratic springs, and show results for different configurations. Even if similar methods have already been proposed, mainly in process control, this approach is novel when applied to robots, and could lead to an overall improvement of their design, exploiting numerical optimization tools, which, in the last years, have become faster and more reliable.",

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N2 - This paper proposes a method to determine the optimal value of design parameters in robots driven by variable-stiffness actuators. The method consists of setting up a nonlinear optimization problem, the solution of which determines the optimal control sequence, and, at the same time, the optimal values of the parameters. As a case study, we analyze a ball-throwing problem for a two-link elbow manipulator actuated by antagonistic quadratic springs, and show results for different configurations. Even if similar methods have already been proposed, mainly in process control, this approach is novel when applied to robots, and could lead to an overall improvement of their design, exploiting numerical optimization tools, which, in the last years, have become faster and more reliable.

AB - This paper proposes a method to determine the optimal value of design parameters in robots driven by variable-stiffness actuators. The method consists of setting up a nonlinear optimization problem, the solution of which determines the optimal control sequence, and, at the same time, the optimal values of the parameters. As a case study, we analyze a ball-throwing problem for a two-link elbow manipulator actuated by antagonistic quadratic springs, and show results for different configurations. Even if similar methods have already been proposed, mainly in process control, this approach is novel when applied to robots, and could lead to an overall improvement of their design, exploiting numerical optimization tools, which, in the last years, have become faster and more reliable.

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