Results 41 to 50 of about 55,967 (217)
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning
The proposed self‐sensorized artificial muscle (SSAM) can sense its length change as small as 0.01 mm via a seamlessly integrated multi‐segment induction coil. The SSAM provides accurate length information regardless of its loadings, driving pressure, or muscle design, adequate for robust data‐driven feedback control.
Houping Wu +6 more
wiley +1 more source
High‐Speed Altitude Regulation With Neuromorphic Camera and Lightweight Embedded Computation
Neuromorphic cameras deliver rapid, high‐dynamic‐range sensing but overwhelm embedded processors at high speeds. This work presents a lightweight, optimized Lucas–Kanade optical flow method with parallelization, gyroscopic derotation, and adaptive event slicing.
Simon L. Jeger +3 more
wiley +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer +2 more
wiley +1 more source
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley +1 more source
Expériences de terrain, terrain d’expérimentation
Le terrain est pour la discipline anthropologique rite d'initiation et légitimation institutionnelle. Ce que l'on a appelé fieldwork, promu par les sociologues de l'école de Chicago, engage à aller in situ se frotter à d’autres manières de faire. C'est ce que B.
openaire +1 more source
Design‐for‐Benchmarking in Soft Robotics: Navigating Component‐System Dichotomy
Soft robotics faces a profound evaluation challenge: the Component‐System Dichotomy, where isolated component tests fail to predict integrated performance. This article presents a systematic survey of critical reporting gaps across actuation, sensing, and control.
Matteo Lo Preti +4 more
wiley +1 more source
Complex dynamics, often avoided in electromechanical design, can enhance soft robotics. We develop durable magnetic soft actuators operating in tunable dynamic regimes, enabling random number generation, stochastic computing, and time‐series prediction.
Eduardo Sergio Oliveros‐Mata +14 more
wiley +1 more source
ABSTRACT Background Outdoor agricultural workers experience significant heat exposure, yet few studies have evaluated whether wearable sensors can reliably measure continuous physiological responses in real field conditions. This pilot study examined the feasibility and predictive utility of core temperature, hydration, heart rate, and movement data ...
Sinan Sousan +10 more
wiley +1 more source

