Abstract: To improve the robustness and efficiency of consumer mobile robot navigation in complex indoor environments, this paper presents a deep reinforcement learning method named SAC-GHULSTM. The ...
Abstract: Traditional trajectory planning algorithms for multi-UAVs face challenges such as difficulty in establishing cooperative mechanisms and poor adaptability to dynamic obstacle environments. To ...
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