Research and Apply Deep Reinforcement Learning Technology to Control Mobile Robot

International Journal of Electrical and Electronics Engineering

© 2021 by SSRG - IJEEE Journal

Volume 8 Issue 4

Year of Publication : 2021

Authors : Roan Van Hoa, Nguyen Duc Dien, Lai Khac Lai

10.14445/23488379/IJEEE-V8I4P106

How to Cite?

Roan Van Hoa, Nguyen Duc Dien, Lai Khac Lai, "Research and Apply Deep Reinforcement Learning Technology to Control Mobile Robot," SSRG International Journal of Electrical and Electronics Engineering, vol. 8,  no. 4, pp. 30-35, 2021. Crossref, https://doi.org/10.14445/23488379/IJEEE-V8I4P106

Abstract:

Today, mobile robots are being strongly developed and widely used in life such as cargo robots, medical robots, wheelchairs for the disabled, etc. However, letting the robot move intelligently in dynamic environments without knowing the map in advance is a new research area of interest by scientists. The paper presents the application of deep reinforcement learning (DRL) to navigate mobile robots in an unknown environment. The system is built on robot operating system (ROS). The simulation results on the Gazebo software have verified the effectiveness of the proposed method.

Keywords:

Robot operating system (ROS), Deep reinforcement learning, Navigation, Simultaneous localization and mapping (SLAM).

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