Deep Reinforcement Learning Based Autonomous Exploration under Uncertainty with Hybrid Network on Graph

This paper mainly focuses on the autonomous exploration of unknown environments for mobile robots with deep reinforcement learning (DRL). To accurately model the environment, an exploration graph is constructed. Then, we propose a novel S-GRU network combing graph convolutional network (GCN) and gated recurrent units (GRU) based on the exploration graph to extract hybrid features. Both the spatial...