Official implementation of R³LIO, a robust and accurate mobile mapping system built upon an iterative error-state Kalman filter (IESKF), targeting a low-cost rotating LiDAR setup (a 16-channel LiDAR actuated by a motor to continuously scan a full FoV).
Launch the real-robot pipeline with:
roslaunch rigelslam_rot run.launchTest on self-recorded sequences:
| “Building“ sequence | “IndustrialPark“ sequence |
| “ParkingLot“ sequence | “OpenSpace“ sequence |
| “CampusLoop“ sequence | “Curved Tunnel“ sequence |
- Start the simulation environment:
roslaunch scout_gazebo test.launch- Start the simulated odometry:
roslaunch rigelslam_rot run_sim.launchTest on simulation sequence:
| Gazebo simulation environment | “SimSq1“ sequence |
The dataset release is currently being organized and will be available soon.
- Self-recorded sequences: coming soon
- Simulation sequences: coming soon
A rough structural design of the device is shown below.
The detailed SolidWorks design files are currently being organized and will be released soon.
If you find this project useful, please consider citing our paper:
Thank the authors of FAST-LIO2 and Scout Gazebo for open-sourcing their outstanding works.