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Department of Mechanical Engineering

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These digital collections include theses, dissertations, faculty publications, and datasets from the Department of Mechanical Engineering.

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Browsing Department of Mechanical Engineering by Author "Abbas, Ali, author"

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    Modeling of twisted and coiled artificial muscle for actuation and self-sensing
    (Colorado State University. Libraries, 2018) Abbas, Ali, author; Zhao, Jianguo, advisor; Bradley, Thomas, committee member; Maciejewski, Anthony, committee member
    Soft robots are a new type of robots with deformable bodies and muscle-like actuations, which are fundamentally different from traditional robots with rigid links and motor-based actuators. Owing to their elasticity, soft robots outperform rigid ones in safety, maneuverability, and adaptability. With their advantages, many soft robots have been developed for manipulation and locomotion in recent years. Nevertheless, two issues prevent the wide applications of developed soft robots: cumbersome actuation methods (e.g., pneumatics) and limited sensing capability to feedback the robot's shape. To address these two issues, this thesis leverages a recently discovered twisted and coiled artificial muscle for soft robots. This artificial muscle can generate large force and displacement; moreover, we recently found that it has self-sensing capability, i.e., its electrical resistance will increase if the muscle is elongated by an external force. With the dual actuation and self-sensing capability, we expect to accomplish closed-loop control of soft robots for precise motion without external sensors, potentially solving the two issues for existing soft robots. This thesis will focus on three aspects for the twisted and coiled artificial muscle. First, we model the actuation from a physics perspective. Such a model utilizes parameters related to the working principle and material properties of the actuator, eliminating the requirements for tedious system identifications. Experiments are conducted to verify the proposed model, and the results demonstrate that the proposed model can predict the static performance and dynamic response for the muscle. Second, we test and model the sensing capability of the artificial muscle. Specifically, we establish a physics-based model to predict the external force and the displacement if the resistance is given and experimentally validate its correctness. Third, we apply the actuation and sensing of the artificial muscle to soft robots. To demonstrate we can leverage the muscle to actuate soft robots, we fabricate a soft manipulator with multiple muscles as well as a robotic fish tail. To demonstrate the sensing capability, we embed the muscle into soft materials and successfully measure two curvatures of a two-segment soft robot. Based on the work presented in this thesis, our future work will integrate the actuation and sensing capability of the twisted and coiled artificial muscle to enable closed-loop shape control of soft robots.