semantic_slam
Real-time 3D semantic mapping system using a handheld RGB-D camera, built on ROS with ORB_SLAM2 and PSPNet.
What is semantic_slam?
Semantic SLAM is a real-time 3D mapping system that builds semantically annotated maps from a handheld RGB-D camera. It solves the problem of environment understanding for robotics by combining simultaneous localization and mapping (SLAM) with deep learning-based semantic segmentation to label objects (e.g., walls, furniture) in the generated 3D map.
Robotics researchers, computer vision engineers, and developers working on autonomous navigation, augmented reality, or environmental modeling who need real-time semantic 3D perception.
It offers an open-source, integrated pipeline for semantic SLAM using commodity hardware, with configurable output (semantic or RGB maps) and multiple fusion methods, built on robust ROS and proven libraries like ORB_SLAM2 and OctoMap.
Overview
Real time semantic slam in ROS with a hand held RGB-D camera
Use Cases
Best For
- Robotic navigation in dynamic indoor environments
- Building 3D semantic maps for augmented reality applications
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
