ORB-SLAM
xtan explores ORB-SLAM related workflows where stereo vision, spatial tracking, and geometry-aware sensing support real-time localization, mapping, and perception systems.
Feature-based visual SLAM systems
ORB-SLAM is one of the most widely used visual SLAM frameworks for real-time camera localization and environment reconstruction. It relies on feature-based visual tracking and geometric relationships between frames to estimate motion and map the environment.
Potential for robotics and spatial navigation
ORB-SLAM is commonly used in robotics, AR systems, research environments, and spatial computing platforms. Stereo camera systems may support experimental pipelines where spatial perception contributes to navigation, mapping, and environment understanding.
Why xtan can be relevant
xtan focuses on stereo vision, geometry-first interaction, and practical spatial systems. Within ORB-SLAM related workflows this may support experimental perception pipelines, spatial mapping systems, and research into geometry-driven localization and navigation.