An optimal Stewart platform for lower extremity robotic rehabilitation

Arman Dabiri, Sahand Sabet, Mohammad Poursina, David G Armstrong, Parviz E Nikravesh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


In this paper, two algorithms are performed to find an optimum design of a six-degree-of-freedom Stewart platform to provide a desired pure rotational motion required in the robotic rehabilitation of the foot for patients with neuropathy. To accomplish this, first, we present the kinematic and the dynamic analysis of the Stewart platform. The dynamic equations are derived by using a customized Lagrange method. Then, physically meaningful objective variables are defined such as the size of the platform, the length of the six links, the maximum stroke of the six linear actuators, the maximum actuator force, and the reachable workspace. This is followed by using two optimization methods (Genetic Algorithm and Monte-Carlo method) to study the aforementioned objective variables, resulting in the optimal solution for the desired orientation motions. Then, the detailed investigation of the effect of changes in these objective variables on the variation of the platform design variables is studied. Finally, in a numerical example, the advantages and disadvantages of using the Genetic Algorithm and the Monte-Carlo method to find the optimal design variables for a custom cost function with weighted objective variables are revealed.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509059928
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2017 American Control Conference, ACC 2017
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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