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Open Access Publications from the University of California

Scholarly Works (3 results)

  • Thesis
  • Peer Reviewed
UC Santa Barbara Electronic Theses and Dissertations (2023)

Beginning in the second half of the 20th century, robots have played a growing role in numerous manufacturing sectors. As we move toward the second quarter of the 21st century, robots are still primarily in the factory, with few successful attempts to address new applications outside the factory -- in less structured environments that require close interaction with humans. In the past decade, soft robotics has emerged as a potential alternative design direction due to its inherent safety and embodied intelligence, but its reduction to practice on a commercial scale has been limited, in part due to the nonlinearity and associated control complexity of soft systems. In this work, we seek to advance the performance of soft robots via insights gained from analytical and data-driven modeling efforts, which enable new design and control capabilities.

We begin by first seeking to understand the fundamental behaviors various soft robotic systems. In Chapter 2, we develop closed-form models of "vine robots," a type of soft, growing robot that changes length by adding material to its tip and their interactions with the environment. Next, we leverage those insights to design novel mechanisms that overcome performance limitations in Chapter 3,developing a novel mechanism that enables vine robots to access larger workspaces.

We then turn to data-driven modeling, leveraging a modern modeling technique to gain physical insights from a continuum soft arm performing dynamic tasks. In Chapter 4, we apply this method to enable accurate control of two soft robot arms in new regimes, controlling inertial motions that allow a soft arm to both catch and throw a ping pong ball.

Finally, in Chapter 5, we describe the culminating work aimed at translating soft robotics to broad commercial application, as we develop the world's first soft robotic intubation system that enables life-saving, expert-level performance in novice hands. While there is yet more work to be done, this body of scientific knowledge will help set the groundwork to advance soft systems into everyday life.

    Cover page: Design, Modeling, and Control of Soft Robots
    • Article
    • Peer Reviewed
    UC Santa Barbara Previously Published Works (2020)
    Soft robots promise improved safety and capability over rigid robots when deployed in complex, delicate, and dynamic environments. However, the infinite degrees of freedom and highly nonlinear dynamics of these systems severely complicate their modeling and control. As a step toward addressing this open challenge, we apply the data-driven, Hankel Dynamic Mode Decomposition (HDMD) with time delay observables to the model identification of a highly inertial, helical soft robotic arm with a high number of underactuated degrees of freedom. The resulting model is linear and hence amenable to control via a Linear Quadratic Regulator (LQR). Using our test bed device, a dynamic, lightweight pneumatic fabric arm with an inertial mass at the tip, we show that the combination of HDMD and LQR allows us to command our robot to achieve arbitrary poses using only open loop control. We further show that Koopman spectral analysis gives us a dimensionally reduced basis of modes which decreases computational complexity without sacrificing predictive power.
      • Article
      • Peer Reviewed
      UC Santa Barbara Previously Published Works (2020)
      In nature, tip-localized growth allows navigation in tightly confined environments and creation of structures. Recently, this form of movement has been artificially realized through pressure-driven eversion of flexible, thin-walled tubes. Here we review recent work on robots that "grow" via pressure-driven eversion, referred to as "everting vine robots," due to a movement pattern that is similar to that of natural vines. We break this work into four categories. First, we examine the design of everting vine robots, highlighting tradeoffs in material selection, actuation methods, and placement of sensors and tools. These tradeoffs have led to application-specific implementations. Second, we describe the state of and need for modeling everting vine robots. Quasi-static models of growth and retraction and kinematic and force-balance models of steering and environment interaction have been developed that use simplifying assumptions and limit the involved degrees of freedom. Third, we report on everting vine robot control and planning techniques that have been developed to move the robot tip to a target, using a variety of modalities to provide reference inputs to the robot. Fourth, we highlight the benefits and challenges of using this paradigm of movement for various applications. Everting vine robot applications to date include deploying and reconfiguring structures, navigating confined spaces, and applying forces on the environment. We conclude by identifying gaps in the state of the art and discussing opportunities for future research to advance everting vine robots and their usefulness in the field.
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