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M. Tropea

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Conference Jul 2026

3D Deep Reinforcement Learning Based UAV Trajectory Planning in Dynamic and Partially Observable Environments

Trajectory planning for unmanned aerial vehicles (UAVs) in dynamic and partially observable environments becomes more complex when extended from two-dimensional to three-dimensional navigation. Although Deep Reinforcement Learning (DRL) methods have shown strong performance in 2D scenarios, their application to 3D spac...

Eduardo Machado Wullner, Arthur von Groll dos Santos, M. Vizzotto et al. · 0 citations
Open access 2026

Energy-Aware Persistent Storage Optimization for Mobile Embedded Edge IoT Platforms

Experimental results show that by using an optimal buffer size, the edge node reduces SPI bus usage for reading and writing data to the SD card from 38.0% to 3.1%, which significantly minimizes delays caused by frequent SD card access and also lowers the edge node’s energy consumption.

L. Campoverde, M. Tropea, F. De Rango · 0 citations

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