Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments

Rescue robots can be used in urban search and rescue (USAR) applications to perform the important task of exploring unknown cluttered environments. Due to the unpredictable nature of these environments, deep learning techniques can be used to perform these tasks. In this letter, we present the first...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 4; H. 2; S. 610 - 617
Hauptverfasser:	Niroui, Farzad, Kaicheng Zhang, Kashino, Zendai, Nejat, Goldie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Autonomous agents Computer architecture Deep learning deep learning in robotics and automation Exploration Layout Layouts Machine learning Microprocessors Navigation Robot sensing systems Robots Search and rescue missions search and rescue robots Task analysis Wideband communications
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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