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Deep reinforcement learning based mobile robot navigation: A review
2021
Tsinghua Science and Technology
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. There is a growing trend of applying DRL to mobile robot navigation. In this paper, we review DRL methods and DRL-based navigation frameworks. Then we systematically compare and analyze the relationship and differences between four typical application scenarios: local obstacle avoidance,
doi:10.26599/tst.2021.9010012
fatcat:7rrkw43mqffdjnmgvxkxjwrhkm