Results 161 to 170 of about 10,080 (259)

Intelligent Agent for Resource Allocation from Mobile Infrastructure to Vehicles in Dynamic Environments Scalable on Demand. [PDF]

Sensors (Basel)
Cumbal R, Arguero B, Arévalo GV, Hincapié R, Tipantuña C.   +4 more
europepmc   +1 more source

A Soft Robotic Jellyfish with Decoupled Actuators for Agile 3D Locomotion

Advanced Intelligent Systems, EarlyView.
This study presents a soft robotic jellyfish featuring a functionally decoupled actuation architecture. By separating propulsion, steering, and vertical regulation into independent modules, the robot overcomes conventional coupled‐motion limitations. Utilizing a passive‐valve‐based differential drag strategy and lateral water jets, it achieves agile 3D
Zhuoheng Li, Ze Huang, Salvador Pané, Josep Puigmartí‐Luis, Jiwan Kim, Ji‐Hun Bae, Bumjin Jang   +6 more
wiley   +1 more source

Research on engine power-loss fault diagnosis method based on time-series data mining. [PDF]

Sci Rep
Feng L, Liu L, Xu H, Gao S, Tang H, Cui J, Zhang B, Rao Y.   +7 more
europepmc   +1 more source

Cteno‐Bot: An Untethered Metachronally Swimming Robot With Magnetoactive Propulsors

Advanced Intelligent Systems, EarlyView.
We present Cteno‐bot, an untethered ctenophore‐inspired robot which swims using metachronally coordinated appendages. A single mechanism controls up to 216 magnetoactive propulsors via a dynamically varying magnetic field. We show that the swimming speed of the robot can be increased without a corresponding increase in power requirement, simply by ...
David J. Peterman, Margaret L. Byron
wiley   +1 more source

When AI takes the wheel: AI-defined vehicles principles and pitfalls. [PDF]

Front Robot AI
De Vincenzi M, Bodei C, Matteucci I.
europepmc   +1 more source

Shapley Additive Explanation for Local Class Differentiation: Local Explainability for Class Differentiation in Classification Models

Advanced Intelligent Systems, EarlyView.
An instance‐level, model‐agnostic explanation of class differentiation is introduced through SHAP‐LCD, linking probability shifts to feature‐wise Shapley contributions. The method operates on tabular and image data and is released in a fully reproducible implementation, offering a transparent way to examine, at each instance, why predictive models ...
Roxana M. Romero Luna, Hugo A. Ordoñez Erazo, Carlos A. Cobos Lozada   +2 more
wiley   +1 more source

Micro-Energy Harvesting and Self-Powered Sensing for Intelligent Road: A Comprehensive Review. [PDF]

Research (Wash D C)
Zheng G, Xing C, Zhang L, Li H, Cheng T, Tan Y.   +5 more
europepmc   +1 more source

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang, Zichao Wang, Zhiwei He, Qingquan Wei, Yong Zuo, Linzhen Nie, Zhishuai Yin   +6 more
wiley   +1 more source

A multi-scenario evaluation of adaptive Fuzzy Logic Algorithms for intelligent traffic signal management in Urban intersections. [PDF]

Sci Rep
Shaheen S, Qadri SSSM, Riaz MB, Martinovic J, Dvorský J, Slaninová K.   +5 more
europepmc   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

Advanced Intelligent Systems, EarlyView.
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti, Weng Buxiu, Petr Trunin, Muhammad Sunny Nazeer, Lucia Beccai, Perla Maiolino, Cecilia Laschi   +6 more
wiley   +1 more source