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Simultaneous localization and mapping using fiducial markers.
ORB_SLAM2 is a visual simultaneous localization and mapping system that tracks camera movement and builds 3D environments from image data. It functions as a real-time visual odometry tool and sparse 3D reconstructor, computing the position and orientation of a camera while generating a point cloud map of a physical space. The system utilizes a camera relocalization engine to identify a camera's position within a known map after tracking failure or system restarts. It incorporates a spatial tracker to enable the precise insertion and composition of virtual 3D objects into real-world planar reg
This project is a framework for autonomous mobile robot navigation within the Robot Operating System ecosystem. It provides a suite of tools for calculating safe trajectories and movement commands, enabling mobile bases to reach specific destinations while avoiding obstacles in dynamic environments. The system utilizes a hierarchical planning approach that separates long-range path generation from short-range reactive obstacle avoidance. It maintains spatial awareness through a centralized coordinate tracking system and a grid-based representation that stores obstacle information and proximit
Direct Sparse Odometry
The main features of jakobengel/dso are: Simultaneous Localization and Mapping, SLAM and Mapping.
Projects with overlapping indexed features include: ubiquityrobotics/fiducials — Simultaneous localization and mapping using fiducial markers. ethz-asl/maplab — A Modular and Multi-Modal Mapping Framework. raulmur/orb_slam2 — ORB_SLAM2 is a visual simultaneous localization and mapping system that tracks camera movement and builds 3D… ros-planning/navigation — This project is a framework for autonomous mobile robot navigation within the Robot Operating System ecosystem. It… cartographer-project/cartographer — Cartographer is a cross-platform robotics library and framework for simultaneous localization and mapping in 2D and 3D… edwardliuyc/staticmapping — Use LiDAR to map the static world.
