Results 221 to 230 of about 233,180 (285)

Adaptive Collision Sensitivity for Efficient and Safe Human–Robot Collaboration

open access: yesAdvanced Intelligent Systems, EarlyView.
An adaptive collision‐sensitivity framework uses each robot link's effective mass to estimate contact forces online and decide when collaborative robots should stop or continue. Tested on simulated and real UR10e and simulated KUKA arms, it maintains conservative force estimates while reducing unnecessary stops and increasing task productivity. What is
Lukas Rustler   +2 more
wiley   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

open access: yesAdvanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica   +38 more
wiley   +1 more source

Designing Wire Mazes for Replicating Natural Echoes to Study Bat Biosonar Function

open access: yesAdvanced Intelligent Systems, EarlyView.
A validated framework combining efficient physical modeling (multiple scattering model) and deep learning is presented to guide wire‐maze design for bat biosonar studies. This approach rapidly generates large datasets to test acoustic distinguishability among wire arrangements.
Chunlin Jia   +3 more
wiley   +1 more source

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou   +5 more
wiley   +1 more source

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

open access: yesAdvanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

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