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Open Access Publications from the University of California

Scholarly Works (7 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2024)

Soft robotics is an emerging field that offers adaptability and flexibility compared to rigid robots due to their inherent elasticity. Unlike rigid robots, soft robots exhibit distinct properties, kinematics and dynamics. This research, therefore, intends to introduce novel advancements in soft gripper design and control. Inspired by human skin, a dual-layer soft tactile sensor is proposed with pyramid-shaped sensing elements. It employs machine learning approaches to achieve superior sensitivity in detecting contact force, contact location, and other features. A novel design methodology for soft pneumatic actuators utilizes simplified cantilever beam approximations to develop kinematic and dynamic models. Model-based optimization design techniques are applied to determine optimal dimensional parameters, enhancing the actuator's properties such as force/torque, bendability, and controllability. To accurately capture nonlinear mechanical behavior, an alternative modeling approach using Ludwick’s Law and data-driven parameter estimation is introduced and validated through experimentation. The approach optimizes the efficiency of parameter determination within dynamical models while improving accuracy. Addressing control challenges in under-actuated systems, this research explores coordination strategies for multiple soft actuators of a soft gripper, employing stable model inversion to a multi-finger soft gripper. Simulation and experimental validation demonstrate the effectiveness of this strategy in achieving precise and coordinated motions, thereby advancing the practical applicability of soft robots. Overall, these techniques aim to enhance the capabilities of current soft grippers, paving the way for their broader deployment in real-world scenarios.

    Cover page: Development of a Soft Gripper - Sensing, Actuation, and Controls
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2023)
    Syringe pump has been applied to actuate soft pneumatic robots. Most previous works focus on designs of the syringe pump, its applications, and improvement of its problems such as leaking air, inefficient motions, etc. This paper introduces dynamical modeling and parametric analysis of a syringe pump. The syringe pump is made of a commercial syringe and a linear actuator. The dynamic equation is derived from the motions of the linear actuator, the air dynamics in the syringe, and the airflow inside the soft actuator. Because of the high-elastic materials, the volume of the soft actuator is a time-varying parameter. Therefore, the variation of volume is estimated by the Kalman filter instead of relying on the traditional design method. The dynamic model is also utilized to select optimal parameters which are verified by the experiments for the syringe pump. Two system controllers are designed with and without consideration of the pressure dynamics. The controller considering pressure dynamics outperforms. This work shows the benefits of pressure dynamic of the syringe pump for both system design and advanced controller design.
      Cover page: Design, Modeling, and Parametric Analysis of a Syringe Pump for Soft Pneumatic ActuatorsCreative Commons 'BY-ND' version 4.0 license
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2023)
      Soft pneumatic actuators are widely used for soft grippers, which are known for their compliance as compared with traditional grippers. The generated force/torque of soft pneumatic actuators directly determines the grasping force. This paper introduces a computationally efficient soft pneumatic actuator (SPA) design methodology. The complex structure of the pneumatic actuator is approximated by a cantilever beam. The relationship between input pressure and output torque is derived by standard mechanical analysis. The design problem is formulated as a model-based optimization problem by treating the input-output mathematical model as the objective function. By solving the optimization problem, the optimal design parameters are obtained. Finite element analysis is applied to preliminarily verify the design parameters without the time-consuming fabrication of many actuators. Three soft actuators with different design parameter sets were fabricated to validate the optimal parameters. This work shows the utility of surprisingly simple calculations and assumptions for rapid parametric design studies.
        Cover page: Mechanical Modeling and Optimal Model-based Design of a Soft Pneumatic ActuatorCreative Commons 'BY-NC-ND' version 4.0 license
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2023)
        This article reports the construction of an articulated manipulator’s hybrid dynamic model and trajectory planning and optimization of the manipulator using deep reinforcement learning (RL) on the dynamic model. The hybrid model was composed of a physical-based reduced-order dynamic model, linear friction and damping terms, and a deep neural network model to compensate for the nonlinear characteristics of the manipulator. The hybrid model then served as the digital twin of the manipulator for trajectory planning to optimize energy efficiency and operation speed by using RL while taking obstacle avoidance into consideration. The proposed strategy was simulated and experimentally validated. The energy consumption along paths was reduced and the speed was increased so the manipulator could achieve more efficient motion.
          Cover page: Manipulator Trajectory Optimization Using Reinforcement Learning on a Reduced-Order Dynamic Model with Deep Neural Network CompensationCreative Commons 'BY-NC-ND' version 4.0 license
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2023)
            Cover page: Control of Soft Pneumatic Actuators with Approximated Dynamical ModelingCreative Commons 'BY-NC-ND' version 4.0 license
            • Article
            • Peer Reviewed
            UC San Diego Previously Published Works (2014)
            Diabetic nephropathy is characterized by excessive deposition of extracellular matrix protein and disruption of the glomerular filtration barrier. Matrix metalloproteinases (MMPs) affect the breakdown and turnover of extracellular matrix protein, suggesting that altered expression of MMPs may contribute to diabetic nephropathy. Here we used an MMP-9 gene knockout mouse model, with in vitro experiments and clinical samples, to determine the possible role of MMP-9 in diabetic nephropathy. After 6 months of streptozotocin-induced diabetes, mice developed markedly increased albuminuria, glomerular and kidney hypertrophy, and thickening of the glomerular basement membrane. Gelatin zymographic analysis and western blotting showed that there was enhanced MMP-9 protein production and activity in the glomeruli. However, MMP-9 knockout in diabetic mice significantly attenuated these nephropathy changes. In cultured podocytes, various cytokines related to diabetic nephropathy including TGF-β1, TNF-α, and VEGF stimulated MMP-9 secretion. Overexpression of endogenous MMP-9 induced podocyte dedifferentiation. MMP-9 also interrupted podocyte cell integrity, promoted podocyte monolayer permeability to albumin, and extracellular matrix protein synthesis. In diabetic patients, the upregulation of urinary MMP-9 concentrations occurred earlier than the onset of microalbuminuria. Thus, MMP-9 seems to play a role in the development of diabetic nephropathy.
              Cover page: Matrix metalloproteinase-9 deficiency attenuates diabetic nephropathy by modulation of podocyte functions and dedifferentiation
              • Article
              • Peer Reviewed
              LBL Publications (2022)
              The practical application of high-capacity lithium-rich cathode materials in lithium-ion batteries has been largely restricted by severe side reactions with electrolytes. Herein, we report a highly stable lithium-rich Li2RuO3 cathode by forming a passivating solid electrolyte interphase at the interface with a sulfide solid electrolyte such as Li6PS5Cl in all-solid-state lithium batteries (ASSLBs), which efficiently suppresses serious parasitic interfacial reactions and fast-increasing interfacial impedance normally observed in liquid electrolytes. The exceptionally high interfacial stability of the Li2RuO3/sulfide electrolyte interface contributes to a high reversible capacity of 257 mA h g−1 of Li2RuO3 at 0.05C rate, and unprecedented cycling stability with 90% capacity retention after 1000 cycles at 1C rate. Comprehensive experimental characterizations and first-principles calculations disclose that electronically insulating interfacial reaction products forming at the interface between the Li2RuO3 cathode and Li6PS5Cl facilitate the formation of a stable and passivating interphase and block the continuous side reactions. Importantly, reversible oxygen redox activity of Li2RuO3 is well-maintained in this configuration of ASSLBs even after 600 cycles, thus the common voltage decay of the Li-rich material is also significantly reduced. These new discoveries demonstrate the critical role of interface design for achieving prolonged cycling stability of lithium-rich cathode materials.
                Cover page: Highly reversible Li 2 RuO 3 cathodes in sulfide-based all solid-state lithium batteriesCreative Commons 'BY-NC' version 4.0 license
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