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DRL for Multi-Robot Path Planning by wiem.belhedi is a document available to read on EtoBox.

The document presents a novel model, DRL-MPC-GNNs, that integrates Deep Reinforcement Learning, Model Predictive Control, and Graph Neural Networks to enhance path planning and task allocation in multi-robot systems. This model addresses challenges such as adaptability, real-time decision-making, and efficiency in complex environments, demonstrating significant improvements in collaboration and performance through rigorous experiments. The research contributes to the field of multi-robot systems by providin

Author
wiem.belhedi
Language
EN