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Design and Control of a Tunable Compliance Actuator

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Biomimetic and Biohybrid Systems (Living Machines 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8608))

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Abstract

TCERA (Tunable Compliance Energy Return Actuator) is a robotic actuator inspired by properties and behavior of the human knee joint, in that it utilizes antagonistic contraction to vary torsional stiffness and joint angle. The actuator is an electrically activated artificial muscle which uses two constant air-mass pneumatic springs configured antagonistically about the knee joint. The positions of the actuator insertion points are controlled in order to change the effective torsional stiffness about the knee axis. Additionally, the rigid member to which the insertion points are attached is able to rotate in order to alter the static equilibrium of the knee system. Furthermore, the system has been simulated and an artificial neural network (ANN) has been trained to determine the control bar angle and attachment location required based on the desired angle, stiffness, and predicted torque state of the joint. Using this controller we have achieved actuator position and stiffness control both with and without load.

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0951783. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Webster, V., Leibach, R., Hunt, A., Bachmann, R., Quinn, R.D. (2014). Design and Control of a Tunable Compliance Actuator. In: Duff, A., Lepora, N.F., Mura, A., Prescott, T.J., Verschure, P.F.M.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2014. Lecture Notes in Computer Science(), vol 8608. Springer, Cham. https://doi.org/10.1007/978-3-319-09435-9_30

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  • DOI: https://doi.org/10.1007/978-3-319-09435-9_30

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09434-2

  • Online ISBN: 978-3-319-09435-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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