Feb. 7, 2024, 5:43 a.m. | Leonardo Spampinato Enrico Testi Chiara Buratti Riccardo Marini

cs.LG updates on arXiv.org arxiv.org

In upcoming 6G networks, unmanned aerial vehicles (UAVs) are expected to play a fundamental role by acting as mobile base stations, particularly for demanding vehicle-to-everything (V2X) applications. In this scenario, one of the most challenging problems is the design of trajectories for multiple UAVs, cooperatively serving the same area. Such joint trajectory design can be performed using multi-agent deep reinforcement learning (MADRL) algorithms, but ensuring collision-free paths among UAVs becomes a critical challenge. Traditional methods involve imposing high penalties during …

acting aerial applications collision cs.lg cs.ma cs.ro design everything mobile multiple networks role trajectory unmanned aerial vehicles vehicles

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