JOURNAL ARTICLE

Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

Abstract

Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. Deep learning provides the mechanism to RL which enables the agent to solve the human level task. The rise of RL begins when a computer player beat the human expert in the most difficult game Go [6]. In this paper, we discuss some important topics such as the general view of reinforcement learning, methods, and algorithms of reinforcement learning and challenges which reinforcement learning is facing. Finally, we discussed a survey of implemented algorithms of RL in the field of robotics for autonomous visual navigation.

Keywords:
Reinforcement learning Computer science Artificial intelligence Robotics Task (project management) Robot Robot learning Deep learning Field (mathematics) Human–computer interaction Machine learning Mobile robot Engineering

Metrics

13
Cited By
0.61
FWCI (Field Weighted Citation Impact)
53
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Reinforcement Learning in Robotics
Physical Sciences →  Computer Science →  Artificial Intelligence
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Multimodal Machine Learning Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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