Abstract: Transfer Learning (TL) is a powerful tool that enables robots to transfer learned policies across different environments, tasks, or embodiments. To further facilitate this process, efforts ...
Abstract: Reinforcement Learning (RL) has shown promise in robotic navigation tasks, yet applying it to real-world environments remains challenging due to dynamic complexities and the need for ...
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