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Abstract: This study introduces an Adaptive Federated Learning (AFL) framework designed to address the challenges of data heterogeneity, resource imbalance, and communication constraints in ...
Energy efficiency alone cannot justify trade-offs that might undermine safety. To ensure robust performance under all conditions, the researchers integrated a reinforcement learning–based decision ...
Abstract: In this paper, a reinforcement learning (RL) control method is developed for the formation control of multiple wheeled mobile robots (WMRs) with visual servoing. First, a multi-robot system ...
In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...