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Related papers: Generative Design of Multimodal Soft Pneumatic Act…

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Mechanical metamaterials actuators achieve pre-determined input--output operations exploiting architectural features encoded within a single 3D printed element, thus removing the need of assembling different structural components. Despite…

Soft Condensed Matter · Physics 2020-09-09 Silvia Bonfanti , Roberto Guerra , Francesc Font Clos , Daniel Rayneau-Kirkhope , Stefano Zapperi

Generative systems have a significant potential to synthesize innovative design alternatives. Still, most of the common systems that have been adopted in design require the designer to explicitly define the specifications of the procedures…

Machine Learning · Computer Science 2019-04-03 Ardavan Bidgoli , Pedro Veloso

Soft pneumatic actuators (SPA) made from elastomeric materials can provide large strain and large force. The behavior of locally strain-restricted hyperelastic materials under inflation has been investigated thoroughly for shape…

Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key characteristic of parametric CAD is that design intent is…

Machine Learning · Computer Science 2022-04-29 Ari Seff , Wenda Zhou , Nick Richardson , Ryan P. Adams

This paper introduces a novel design method that enhances the force/torque, bendability, and controllability of soft pneumatic actuators (SPAs). The complex structure of the soft actuator is simplified by approximating it as a cantilever…

Robotics · Computer Science 2024-04-16 Wu-Te Yang , Burak Kurkcu , Masayoshi Tomizuka

The design of robots that are light, soft, powerful is a grand challenge. Since they can easily adapt to dynamic environments, soft robotic systems have the potential of changing the status-quo of bulky robotics. A crucial component of soft…

Systems and Control · Computer Science 2018-04-06 Nafiseh Ebrahimi , Sebastian Nugroho , Ahmad F. Taha , Nikolaos Gatsis , Wei Gao , Amir Jafari

Rigid-bodied robots often lack compliance needed to adapt to unstructured environments, while fully soft robots, though highly adaptable, struggle with scalability and load capacity. In nature, musculoskeletal systems balance strength and…

Computational Engineering, Finance, and Science · Computer Science 2026-05-29 Hiroki Kobayashi , Yuki Takaha , Changyoung Yuhn , Yuki Sato , Sunao Tomita , Atsushi Kawamoto , Tsuyoshi Nomura

Soft robotic systems are known for their flexibility and adaptability, but traditional physics-based models struggle to capture their complex, nonlinear behaviors. This study explores a data-driven approach to modeling the…

Tendon-driven continuum robot kinematic models are frequently computationally expensive, inaccurate due to unmodeled effects, or both. In particular, unmodeled effects produce uncertainties that arise during the robot's operation that lead…

Robotics · Computer Science 2024-04-08 Jordan Thompson , Brian Y. Cho , Daniel S. Brown , Alan Kuntz

This paper presents a novel generative model to synthesize fluid simulations from a set of reduced parameters. A convolutional neural network is trained on a collection of discrete, parameterizable fluid simulation velocity fields. Due to…

Machine Learning · Computer Science 2019-09-05 Byungsoo Kim , Vinicius C. Azevedo , Nils Thuerey , Theodore Kim , Markus Gross , Barbara Solenthaler

To facilitate the antenna design with the aid of computer, one of the practices in consumer electronic industry is to model and optimize antenna performances with a simplified antenna geometric scheme. Traditional antenna modeling requires…

Machine Learning · Computer Science 2022-03-23 Yang Zhong , Peter Renner , Weiping Dou , Geng Ye , Jiang Zhu , Qing Huo Liu

While its biological significance is well-documented, its application in soft robotics, particularly for the transport of fragile and irregularly shaped objects, remains underexplored. This study presents a modular soft robotic actuator…

Robotics · Computer Science 2024-12-11 Brian Ye , Zhuonan Hao , Priya Shah , Mohammad Khalid Jawed

Generative systems are becoming a crucial part of current design practice. There exist gaps however, between the digital processes, field data and designer's input. To solve this problem, multiple processes were developed in order to…

Graphics · Computer Science 2023-12-22 Demircan Tas , Osman Sumer

Variable stiffness actuator (VSA) designs are manifold. Conventional model-based control of these nonlinear systems is associated with high effort and design-dependent assumptions. In contrast, machine learning offers a promising…

Systems and Control · Electrical Eng. & Systems 2024-04-17 Tim-Lukas Habich , Sarah Kleinjohann , Moritz Schappler

Modeling biological soft tissue is complex in part due to material heterogeneity. Microstructural patterns, which play a major role in defining the mechanical behavior of these tissues, are both challenging to characterize, and difficult to…

Machine Learning · Computer Science 2022-07-19 Hiba Kobeissi , Saeed Mohammadzadeh , Emma Lejeune

Soft robotic grasping has rapidly spread through the academic robotics community in recent years and pushed into industrial applications. At the same time, multimaterial 3D printing has become widely available, enabling the monolithic…

Robotics · Computer Science 2023-03-16 Josh Pinskier , Prabhat Kumar , Matthijs Langelaar , David Howard

The rapidly advancing fields of statistical modeling and machine learning have significantly enhanced data-driven design and optimization. This paper focuses on leveraging these design algorithms to optimize a medical walker, an integral…

Machine Learning · Computer Science 2023-10-31 Advaith Narayanan

Accurate kinematic models are essential for effective control of surgical robots. For tendon driven robots, which is common for minimally invasive surgery, intrinsic nonlinearities are important to consider. Traditional analytical methods…

Robotics · Computer Science 2020-06-11 Francesco Cursi , Anh Nguyen , Guang-Zhong Yang

Exploring the design and control strategies of soft robots through simulation is highly attractive due to its cost-effectiveness. Although many existing models (e.g., finite element analysis) are effective for simulating soft robotic…

Robotics · Computer Science 2024-08-21 Dezhong Tong , Zhuonan Hao , Mingchao Liu , Weicheng Huang

This study introduces a generative imputation model leveraging graph attention networks and tabular diffusion models for completing missing parametric data in engineering designs. This model functions as an AI design co-pilot, providing…

Machine Learning · Computer Science 2024-06-19 Rui Zhou , Chenyang Yuan , Frank Permenter , Yanxia Zhang , Nikos Arechiga , Matt Klenk , Faez Ahmed