@Article{cmc.2026.085054,
AUTHOR = {Yaolei Wang, Wangyan Li, Guoliang Wei},
TITLE = {Recent Advances in UAV-Based SLAM: A Survey},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/cmc/online/detail/27632},
ISSN = {1546-2226},
ABSTRACT = {With the rapid development of <i>unmanned aerial vehicle</i> (UAV) technologies, <i>simultaneous localization and mapping</i> (SLAM) has emerged as a key enabling paradigm for autonomous navigation and environmental perception. This paper presents a comprehensive survey of recent trends in UAV-based SLAM. First, we review the fundamental components of UAV-based SLAM systems, including commonly used onboard sensors and front-end odometry methods such as visual odometry, visual-inertial odometry, and LiDAR-inertial odometry, which provide reliable ego-motion estimation. Next, we summarize back-end methodologies that enhance estimation accuracy and global consistency, covering pose graph optimization, 3D reconstruction techniques, filter-based SLAM, fusion-based multi-UAV SLAM, and emerging blockchain-enabled frameworks for secure and distributed mapping. Furthermore, representative application scenarios are discussed, including a newly proposed category of collaborative UAV-SLAM platforms, termed the UAV-plus system. We also identify several remaining research gaps and highlight future research directions, including observability challenges, operation in imperfect and dynamic environments, and the miniaturization of UAV-based SLAM systems.},
DOI = {10.32604/cmc.2026.085054}
}