Intelligent Sensing to Action for Robust Edge Autonomy
Автор: AI Papers
Загружено: 2025-02-15
Просмотров: 7
Описание:
This paper investigates optimizing "sensing-to-action" loops in autonomous edge computing, which are crucial for real-time decision-making in robotics and similar applications. It addresses challenges like resource limitations and cascading errors by exploring strategies that include proactive, context-aware adaptations. The authors propose techniques, including generative sensing, action-to-sensing optimization, and robust monitoring, to enhance efficiency and reliability. Neuromorphic computing and multi-agent systems are also examined as frameworks for optimizing resource use and improving collaboration. The paper highlights the importance of end-to-end co-design strategies to align algorithmic models with hardware and environmental dynamics for energy-efficient edge autonomy.
https://arxiv.org/pdf/2502.02692
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