Soft Bending Actuator With Fiber-Jamming Variable Stiffness and Fiber-Optic Proprioception

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With the ongoing journey of automation advancements and a trend towards miniaturization, the choice of actuator plays a crucial role. Over recent years, soft actuators have demonstrated their usefulness in various applications, especially where light weigh ...

Bridging the performance gap between robotics and biological systems demands significant advancements across multiple domains, including mechanical design, control theory, modeling, and artificial intelligence. In this thesis, I will introduce innovative m ...

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In recent years, soft robotics has surged in applications like wearables, drones, smart fabrics, and medical instruments. Due to their compliance, these devices excel in tasks demanding dexterity and adaptability, such as manipulation, locomotion, crash re ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

Dielectric elastomer actuators (DEAs) have raised interest due to their remarkable capabilities in various applications, such as soft robotics, haptic feedback systems, and biomedical devices. To harness the full potential of DEAs, the choice of the electr ...

Soft robots are being increasingly developed and deployed for underwater applications such as exploration, monitoring, and rescue owing to their innate compliance, mechanical and chemical stability, and waterproof properties. However, they are still predom ...

The use of soft and stretchable materials allows the development of adaptive robotic systems and human-machine interfaces that are more natural and comfortable to interact with. One of the application fields that benefits the most from these compliant mate ...

We report a soft actuator that generates continuous rotation of an object placed on it by electromagnetically exciting circular travelling waves in a soft disk. The disk, that serves as the stator, is made of a stretchable composite consisting of segments ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

For the EU DEMO conductor testing, a temperature sensor based on Fiber Bragg Grating (FBG) optical fiber is studied at the EPFL Swiss Plasma Center. The SULTAN test facility has been upgraded to use fiber optic sensor for temperature monitoring and quench ...

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

We present a finite elements-neural network approach for the numerical approximation of parametric partial differential equations. The algorithm generates training data from finite element simulations, and uses a data -driven (supervised) feedforward neura ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Soft Bending Actuator With Fiber-Jamming Variable Stiffness and Fiber-Optic Proprioception

Chattez avec Graph Search

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