RL and ANN Based Modular Path Planning Controller for Resource-Constrained Robots in the Indoor Complex Dynamic Environment
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DOI: 10.1109/access.2018.2882875
Abstract: Traditional Reinforcement Learning (RL) approaches are designed to work well in static environments. In many real-world scenarios, the environments are complex and dynamic, in which the performance of traditional RL approaches may drastically degrade. One… read more here.
Keywords: resource constrained; complex dynamic; constrained robots; environment ... See more keywords