RGB-D / stereo / LiDAR graph SLAM with appearance-based loop closure and memory management for real-time large-scale and long-term mapping — the go-to open-source 3D SLAM for camera-equipped robots.
RGB-D / stereo / LiDAR graph SLAM with appearance-based loop closure and memory management for real-time large-scale and long-term mapping — the go-to open-source 3D SLAM for camera-equipped robots.
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RTAB-Map (Real-Time Appearance-Based Mapping) is a graph-SLAM library built around a bag-of-words loop-closure detector and a memory-management scheme that bounds online computation, enabling long-term and large-scale mapping in real time. It fuses RGB-D cameras, stereo rigs, 3D/2D LiDAR, IMU and GPS; produces dense point-cloud maps, OctoMaps, 2D occupancy grids and textured meshes; and ships first-class ROS 1/ROS 2 integration (rtabmap_ros) plus standalone desktop tooling. Developed since 2013 at IntRoLab, Université de Sherbrooke, it is among the most-used visual SLAM systems for AMRs, inspection robots and handheld scanning.
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