Spatial mapping: Difference between revisions
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Depending on the primary sensors used, SLAM can be categorized into several types: | Depending on the primary sensors used, SLAM can be categorized into several types: | ||
* '''Visual SLAM (vSLAM)''': Uses one or more cameras to track visual features.<ref name="MathWorksSLAM"/> | * '''[[Visual SLAM]] (vSLAM)''': Uses one or more cameras to track visual features.<ref name="MathWorksSLAM"/> | ||
* '''LiDAR SLAM''': Uses a LiDAR sensor to build a precise geometric map.<ref name="MathWorksSLAM"/> | * '''[[LiDAR SLAM]]''': Uses a LiDAR sensor to build a precise geometric map.<ref name="MathWorksSLAM"/> | ||
* '''Multi-Sensor SLAM''': Fuses data from various sources (e.g., cameras, IMU, LiDAR) for enhanced robustness and accuracy.<ref name="MathWorksSLAM"/> | * '''[[Multi-Sensor SLAM]]''': Fuses data from various sources (e.g., cameras, IMU, LiDAR) for enhanced robustness and accuracy.<ref name="MathWorksSLAM"/> | ||
Spatial mapping is typically accomplished via SLAM algorithms, which build a map of the environment in real time while tracking the device's position within it.<ref name="Adeia">{{cite web |url=https://adeia.com/blog/spatial-mapping-empowering-the-future-of-ar |title=Spatial Mapping: Empowering the Future of AR |publisher=Adeia |date=2022-03-02 |access-date=2025-10-27}}</ref> | Spatial mapping is typically accomplished via SLAM algorithms, which build a map of the environment in real time while tracking the device's position within it.<ref name="Adeia">{{cite web |url=https://adeia.com/blog/spatial-mapping-empowering-the-future-of-ar |title=Spatial Mapping: Empowering the Future of AR |publisher=Adeia |date=2022-03-02 |access-date=2025-10-27}}</ref> | ||