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A Systematic Design Selection Methodology for System-Optimal Compliant Actuation

Published online by Cambridge University Press:  29 November 2018

Abdullah Kamadan*
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey E-mails: [email protected]; [email protected]
Gullu Kiziltas
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey E-mails: [email protected]; [email protected]
Volkan Patoglu
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey E-mails: [email protected]; [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

This work presents a systematic design selection methodology that utilizes a co-design strategy for system-level optimization of compliantly actuated robots that are known for their advantages over robotic systems driven by rigid actuators. The introduced methodology facilitates a decision-making strategy that is instrumental in making selections among system-optimal robot designs actuated by various degrees of variable or fixed compliance. While the simultaneous co-design method that is utilized throughout guarantees systems performing at their full potential, a homotopy technique is used to maintain integrity via generation of a continuum of robot designs actuated with varying degrees of variable and fixed compliance. Fairness of the selection methodology is ensured via utilization of common underlying (variable) compliant actuation principle and dynamical task requirements throughout the generated system designs. The direct consequence of the developed methodology is that it allows robot designers make informed selections among a variety of systems which are guaranteed to perform at their best. Applicability of the introduced methodology has been validated using a case study for system-optimal design of an active knee prosthesis that is driven by a mechanically adjustable compliance and controllable equilibrium position actuator (MACCEPA) under a periodic/real-life dynamical task.

Type
Articles
Copyright
Copyright © Cambridge University Press 2018 

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