Results 151 to 160 of about 391,445 (269)

Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness

open access: yesAdvanced Intelligent Systems, EarlyView.
Intravascular electroencephalography (ivEEG) using micro‐intravascular electrodes was developed. Cortical‐vein ivEEG showed a higher signal‐to‐noise ratio and finer spatial resolution of somatosensory evoked potentials (SEPs) than superior sagittal sinus ivEEG, and deep‐vein ivEEG captured clear visual evoked potentials.
Takamitsu Iwata   +15 more
wiley   +1 more source

Elastic Fast Marching Learning from Demonstration

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados   +3 more
wiley   +1 more source

Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial‐Ground Robotic System

open access: yesAdvanced Intelligent Systems, EarlyView.
A hierarchical multimodal framework coupling a large language model for task decomposition and semantic mapping with a fine‐tuned vision‐language model for semantic perception, enhanced by GridMask, is presented. An aerial‐ground robot team exploits the semantic map for global and local planning.
Haokun Liu   +6 more
wiley   +1 more source

Soft Robotic Sim2Real via Conditional Flow Matching

open access: yesAdvanced Intelligent Systems, EarlyView.
A new framework based on conditional flow matching addresses the persistent Sim2Real gap in soft robotics. By learning a conditional probability path, the model directly transforms inaccurate simulation data to match physical reality, successfully capturing complex phenomena like hysteresis.
Ge Shi   +6 more
wiley   +1 more source

Bridging High‐Fidelity Simulations and Physics‐Based Learning using a Surrogate Model for Soft Robot Control

open access: yesAdvanced Intelligent Systems, EarlyView.
A surrogate‐model‐based framework is proposed for combining high‐fidelity finite element method and efficient physics simulations to enable fast, accurate soft robot simulation for reinforcement learning, validated through sim‐to‐real experiments. Soft robotics holds immense promise for applications requiring adaptability and compliant interactions ...
Taehwa Hong   +3 more
wiley   +1 more source

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