A basic SLAM system that employs 2D and 3D LIDAR measurements
- Class for handling 6 DOF poses, with time stamp, position, rotation and covariance.
- Handle robot odometry.
- Handle absolute robot pose from Gazebo.
- Estimate odometry using ICP on LIDAR measurements.
- Cloud skipping for coping with sensors with high output frequency.
- Mapping
- Implement a class to handle the current map with an Octree.
- Localization on currently built map. (inspiration: BLAM!)
- Pose graph optimization
- Abstract class for pose optimization.
- Visualization with ROS markers.
- Integrate g2o.
- Integrate GTSAM.
- Basic pose graph with ICP transforms. ("Smoothing")
- Integrate wheel odometry.
- Technical improvements
- Make odometry, localization and mapping nodes run concurrently.
- Make everything thread safe.
- Wiki
- Installation.
- Parameters.
- ROS nodes.
- Examples of use.