3D Object Capture im Vergleich zu RTAB-Map - 3D LiDAR Scanner Nutzung und Statistiken

RTAB-Map (Real-Time Appearance-Based Mapping) is an Open Source LiDAR / RGB-D / Stereo Graph-Based SLAM (Simultaneous Localization and Mapping) approach based on an online incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determinate how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map's graph, then a graph optimizer minimizes the errors in the map in real-time. An optional memory management approach can be used to limit the number of locations used for loop closure detection and graph optimization, so that real-time constraints on large-scale environnements are always respected. ARKit's visual inertial odometry (VIO) is used as the SLAM front-end for RTAB-Map (the SLAM back-end). * Note that unlike other scanning apps that optimize the map only after mapping, with RTAB-Map you get loop closure detection and map optimization online so you can have a live feedback to know when you have enough constraints in the map for good global optimization before stopping the scan. *** 3D reconstruction available only with LiDAR sensor. Features: * Online 3D scanning/mapping of the environment. * Online loop closure detection and map correction. * Save in DB format (RTAB-Map desktop and rtabmap_ros format). * Export in PLY, LAS or OBJ. * Multi-session mapping (save and continue later). * Use Apriltags to help finding loop closures in textureless environments. * Mixed AR/VR First-Person in visualization mode. * Raw ARKit data recording (up to 60 Hz!), useful to record long sessions without comprising battery life.