Massive Parallel Deep Reinforcement Learning for Active SLAM
Massive Parallel Deep Reinforcement Learning for Active SLAM explores A scalable end-to-end DRL framework for Active SLAM that significantly reduces training time and supports continuous action spaces.. Commercial viability score: 4/10 in Robotics.
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