Results 161 to 170 of about 4,588,527 (293)

On‐Chip Photonic Neural Network Architectures

open access: yesAdvanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong   +7 more
wiley   +1 more source

Wavelength‐Multiplexed 2D Beam Steering via a Passive Diffractive Network

open access: yesAdvanced Optical Materials, EarlyView.
Illustration of a wavelength‐multiplexed diffractive beam steering system, which is composed of K cascaded diffractive layers, each containing phase‐modulating elements that are jointly optimized using deep learning–based optimization. When illuminated with a set of wavelengths {λ1,λ2,…,λNw}$\{ {{{\lambda }_1},{{\lambda }_2},\ldots ,{{\lambda }_{{{N}_w}
Che‐Yung Shen   +5 more
wiley   +1 more source

From Rigid to Soft Robotic Approaches for Neuroendoscopy

open access: yesAdvanced Robotics Research, EarlyView.
Robotic assistance has had minimal impact on deep intraventricular surgeries, where small‐scale, precision, and reduced invasiveness can contribute to improved patient outcomes. Emerging technologies in rigid, soft, and hybrid robotics are reviewed to identify the most promising mechanisms for deep brain navigation in addition to an attempt to identify
Kieran Gilday   +3 more
wiley   +1 more source

Strong‐Magnetic Flexible Composites for Magnetically Responsive Soft Robots

open access: yesAdvanced Robotics Research, EarlyView.
This perspective provides an overview of the performance mechanisms, preparation methods, and applications of strong magnetic flexible composite materials in soft actuators (such as gripping, movement, and sensing), and further explores current opportunities and challenges.
Wenwen Li   +4 more
wiley   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

open access: yesAdvanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat   +4 more
wiley   +1 more source

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