期刊
GEO-SPATIAL INFORMATION SCIENCE
卷 21, 期 1, 页码 21-32出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/10095020.2017.1420509
关键词
Unmanned aerial vehicles (UAV); visual SLAM; obstacle avoidance; path planning
资金
- National Natural Science Foundation of China [61771350]
- Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences [LSU-SJLY-2017-01]
- Open Research Fund of State Key Laboratory of Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing [2016-ZW-KFJJ02]
Research on unmanned aerial vehicles (UAV) has been increasingly popular in the past decades, and UAVs have been widely used in industrial inspection, remote sensing for mapping & surveying, rescuing, and so on. Nevertheless, the limited autonomous navigation capability severely hampers the application of UAVs in complex environments, such as GPS-denied areas. Previously, researchers mainly focused on the use of laser or radar sensors for UAV navigation. With the rapid development of computer vision, vision-based methods, which utilize cheaper and more flexible visual sensors, have shown great advantages in the field of UAV navigation. The purpose of this article is to present a comprehensive literature review of the vision-based methods for UAV navigation. Specifically on visual localization and mapping, obstacle avoidance and path planning, which compose the essential parts of visual navigation. Furthermore, throughout this article, we will have an insight into the prospect of the UAV navigation and the challenges to be faced.
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