googlecartographer/cartographer
Cartographer
Cartographer is a software library and spatial localization engine for simultaneous localization and mapping. It provides a framework for calculating the precise position and orientation of a device while concurrently generating real-time 2D and 3D representations of its environment using lidar-based data.
The system implements a real-time mapping approach that uses live sensor streams to track device heading and position. It utilizes a submap-based mapping strategy to divide environments into local maps that are aligned into a global map.
The project covers a range of SLAM capabilities, including loop-closure detection to correct mapping errors, pose graph optimization to minimize sensor drift, and multi-sensor data fusion. It further employs probabilistic grid mapping and scan-to-submap matching to derive environmental occupancy and sensor poses.
Features
- Real-Time SLAM - Provides a real-time SLAM engine that builds maps and tracks device position using live sensor streams.
- Loop Closure Detection - Provides loop-closure detection to identify previously visited locations and correct large-scale mapping errors.
- Sensor Fusion - Combines high-frequency IMU data with LiDAR scans for robust motion tracking and environmental modeling.
- Simultaneous Localization and Mapping - Builds environmental maps and tracks device position in 2D or 3D using live sensor streams.
- SLAM Frameworks - Acts as a comprehensive software framework for implementing simultaneous localization and mapping using LiDAR sensors.
- 2D and 3D Environmental Mapping - Generates real-time 2D and 3D representations of the environment to enable device spatial awareness.
- Pose Graph Optimizations - Implements pose graph optimization to minimize accumulated sensor drift for more accurate mapping.
- Real-Time Spatial Mapping Systems - Implements a system that generates spatial environmental representations and tracks device position using live sensor streams.
- Robot Localization and Mapping - Calculates the precise position and orientation of a device within a map for autonomous navigation.
- Spatial Localization Engines - Provides an engine that determines the exact heading and position of a device by matching sensor data to maps.
- Spatial Mapping - Enables the generation of real-time 2D or 3D representations of an environment using incoming sensor data.
- Submap-Based Mapping - Divides the environment into small, independently managed local submaps that are aligned into a global map.
- Lidar Mapping - Uses LiDAR-based data to calculate precise device location and orientation within a mapped environment.
- Probabilistic Occupancy Grids - Represents environmental occupancy using probabilistic grids derived from sensor measurements.
- Device Orientation Tracking - Calculates the exact location and heading of a device within a map through simultaneous localization.
- Scan-to-Submap Matching - Calculates the relative pose of the sensor by aligning current laser scans against local probabilistic grids.
- Device Position Tracking - Calculates the precise position of a device within an environment using localization and mapping algorithms.
- SLAM and Mapping - Library for 2D and 3D SLAM across multiple platforms.
Star history
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