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An overview of simultaneous localisation and mapping: towards multi-sensor fusion

Jun Yin, Fei Yan, Yisha Liu, Guojian He, Yan Zhuang

发表年份
2023
引用次数
27

摘要

Simultaneous localisation and mapping (SLAM) systems have been widely studied over the past 30 years and extensively applied in various fields such as mobile robotics, augmented reality, and virtual reality. The goal of the SLAM technique is to simultaneously map the surrounding environment and obtain the ego-motion of the sensing platform. As the number of application scenarios of SLAM systems increases and related tasks become more complex, SLAM systems based on a single sensor are no longer sufficient to meet the demands, thus the trend for SLAM systems based on multi-sensor fusion has emerged. In this paper, we review the SLAM systems from the perspective of various configurations of heterogeneous sensors. These configurations include visual-inertial, lidar-inertial, lidar-visual, lidar-visual-inertial, and other multi-sensor fusion systems. In addition, the advantages and disadvantages of each configuration are also given. Based on the review, several open issues for further research are discussed at the end of this paper.

关键词

Simultaneous localization and mappingArtificial intelligenceComputer visionLidarComputer scienceRoboticsSensor fusionInertial measurement unitAugmented realityInertial frame of reference

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