同时定位和映射
人工智能
计算机视觉
激光雷达
计算机科学
机器人学
传感器融合
惯性测量装置
增强现实
惯性参考系
移动机器人
机器人
地理
遥感
量子力学
物理
作者
Jun Yin,Fei Yan,Yisha Liu,Guojian He,Yan Zhuang
标识
DOI:10.1080/00207721.2023.2282409
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI