Results 221 to 230 of about 1,903,201 (339)

Piezoresistivity Enhancement by Graphite Flake Alignment in Thin Composite Films for Dielectric Elastomer Switches

open access: yesAdvanced Robotics Research, EarlyView.
This article presents dielectric elastomer switch (DES) materials, based on composite thin films. Alignment of graphite flakes due to their physical confinement within the thin films lead to much stronger piezoresistive responses than bulk composites, while their durability exceeds that of conventional liquid‐based DES materials.
Lingyu Liu   +3 more
wiley   +1 more source

Formation Control of Multi‐Agent System with Local Interaction and Artificial Potential Field

open access: yesAdvanced Robotics Research, EarlyView.
This article proposes a local interaction‐based formation control method for Multi‐Agent system, integrating consensus and leader‐follower strategies with a stress response mechanism—artificial potential field to reduce communication overhead and enable obstacle avoidance. Experimental results on triangular, square, and hexagonal formations confirm its
Luoyin Zhao   +3 more
wiley   +1 more source

RPI-PLMGNN: Enhancing RNA-Protein Interaction Prediction with the Pre-trained Large Language Models and Graph Neural Networks

open access: green
Yulian Jia   +10 more
openalex   +1 more source

Auto‐Routing Fluidic Printed Circuit Boards

open access: yesAdvanced Robotics Research, EarlyView.
This work introduces (STREAM) software tool for routing efficiently advanced macrofluidics, an open‐source software tool for automating the design of 3D‐printable fluidic circuit boards. STREAM streamlines tube routing and layout, enabling the rapid fabrication of fluidic networks for soft robotics, lab‐on‐a‐chip devices, microfluidics, and biohybrid ...
Savita V. Kendre   +3 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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