iNAV-drlSLAM: An Improved Indoor Self-Driving Framework for Mobile Robots using Deep Reinforcement Learning integrated with SLAM

We introduce a new navigation framework for mobile robots that combines Simultaneous Localization and Mapping (SLAM) and deep reinforcement learning (DRL) techniques. While SLAM algorithms are effective at mapping and navigating through the environment, they struggle to avoid dynamic obstacles and c...

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Vydané v:	2023 15th International Conference on Advanced Computational Intelligence (ICACI) s. 1 - 8
Hlavní autori:	Nam, Seunghyeop, Woo, Changseok, Kang, Sinkyu, Nguyen, Tuan Anh, Min, Dugki
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 06.05.2023
Predmet:	Autonomy Deep learning Deep Reinforcement Learning Heuristic algorithms Indoor Self-navigation Inference algorithms Mobile Robot Navigation Q-learning Scalability Simultaneous localization and mapping
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