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#digital-twin News & Analysis

6 articles tagged with #digital-twin. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

6 articles
AIBullisharXiv – CS AI · Mar 96/10
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XR-DT: Extended Reality-Enhanced Digital Twin for Safe Motion Planning via Human-Aware Model Predictive Path Integral Control

Researchers developed XR-DT, an Extended Reality-enhanced Digital Twin framework that combines augmented, virtual, and mixed reality to improve human-robot interaction in shared workspaces. The system uses a novel Human-Aware Model Predictive Path Integral control model with ATLAS, a Transformer-based trajectory prediction system, to enable safer and more interpretable robot navigation around humans.

AIBullisharXiv – CS AI · Mar 36/109
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Information-Theoretic Framework for Self-Adapting Model Predictive Controllers

Researchers introduced Entanglement Learning (EL), an information-theoretic framework that enhances Model Predictive Control (MPC) for autonomous systems like UAVs. The framework uses an Information Digital Twin to monitor information flow and enable real-time adaptive optimization, improving MPC reliability beyond traditional error-based feedback systems.

AIBullisharXiv – CS AI · Mar 26/1017
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Data Driven Optimization of GPU efficiency for Distributed LLM Adapter Serving

Researchers developed a data-driven pipeline to optimize GPU efficiency for distributed LLM adapter serving, achieving sub-5% throughput estimation error while running 90x faster than full benchmarking. The system uses a Digital Twin, machine learning models, and greedy placement algorithms to minimize GPU requirements while serving hundreds of adapters concurrently.

AINeutralarXiv – CS AI · Mar 34/106
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Multi-Condition Digital Twin Calibration for Axial Piston Pumps : Compound Fault Simulation

Researchers developed a multi-condition digital twin calibration framework for axial piston pumps that can simulate compound faults and enable zero-shot fault diagnosis. The physics-data coupled approach addresses data scarcity issues in traditional fault detection methods and demonstrates accurate reproduction of both single and compound faults in hydraulic systems.

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