Results 91 to 100 of about 14,235 (282)

Vision‐Augmented Wearable Interfaces: Bioinspired Approaches for Realistic AI‐Human‐Machine Interaction

open access: yesAdvanced Materials Technologies, EarlyView.
This review presents recent progress in vision‐augmented wearable interfaces that combine artificial vision, soft wearable sensors, and exoskeletal robots. Inspired by biological visual systems, these technologies enable multimodal perception and intelligent human–machine interaction.
Jihun Lee   +4 more
wiley   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

open access: yesAdvanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari   +4 more
wiley   +1 more source

D-ViNE: Dynamic Virtual Network Embedding in Non-Terrestrial Networks

open access: yes, 2022
peer reviewedIn this paper, we address the virtual network embedding (VNE) problem in non-terrestrial networks (NTNs) enabling dynamic changes in the virtual network function (VNF) deployment to maximize the service acceptance rate and service revenue ...
VU, Thang Xuan   +3 more
core   +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

A distributed, parallel, and generic virtual network embedding framework

open access: yes, 2013
One of the main challenges of network virtualization is the mapping of virtual network demands to physical network resources, commonly known as the virtual network embedding (VNE) problem.
Xavier Hesselbach   +9 more
core   +1 more source

Green virtual network embedding in optical OFDM cloud networks [PDF]

open access: yes, 2014
Network virtualization has been identified as the mainstay of the current and future success of cloud computing networks. In this work, we study Virtual Network Embedding (VNE) over Optical Orthogonal Frequency Division Multiplexing (O-OFDM) networks as ...
Elmirghani, JMH   +5 more
core   +1 more source

Information Transmission Strategies for Self‐Organized Robotic Aggregation

open access: yesAdvanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng   +5 more
wiley   +1 more source

An edge-based approach for virtual network embedding based on the graph edit distance. [PDF]

open access: yesPLoS One, 2023
Xu Z   +6 more
europepmc   +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

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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