Outlier-RObust RAdar odometry (ORORA)

animated

:bookmark_tabs: About ORORA (IRCA'23)

A robust radar odometry method in urban environments
Please refer our paper and YouTube for detailed explanations and experimental results!
Validated on MulRan dataset.

Requirement Version & Test Environment

CMake version > 3.13
gcc/g++ > 9.0
In Ubuntu 18.04, we use
- Eigen 3.3
- Boost 1.5.8
- OpenCV 3.3 (or 3.4)
In Ubuntu 20.04, we use
- Eigen 3.3
- Boost 1.71
- OpenCV 4.2

How to Build

Just follow the below command:

$ mkdir -p \~/catkin_ws/src/ && cd \~/catkin_ws/src
$ git clone https://github.com/url-kaist/outlier-robust-radar-odometry.git
$ cd ..
$ catkin build orora

TMI: Following the philosophy of target-oriented CMake, PMC is automatically installed when you run catkin build orora

How to Run and Evaluate Radar Odometry in MulRan dataset

Set file tree of the MulRan dataset as follows:

${MULRAN_DIR}
_____/KAIST03 
     |___global_pose.csv
     |___/gt (Synchonized GT poses are saved)
         |___... 
     |___polar_oxford_form
         |___1567410201812840928.png
         |___1567410202062436262.png
         |___1567410202312110509.png
         |___...    
_____${OTHER SEQ}
     |...
_____...

Generate synchronized ground truth poses to the radar data as follows:

$ rosrun orora mulran_generate_gt ${MULRAN_DIR} ${SEQ1} ${SEQ2}...
// e.g.
$ rosrun orora mulran_generate_gt /media/hyungtaelim/UX960NVMe/mulran KAIST03

Then, set right seq_dir in launch/run_orora.launch & run the below command

roslaunch orora run_orora.launch seq_dir:=${DATA_DIR}

For instance, it can be run as follows:

roslaunch orora run_orora.launch seq_dir:="/media/shapelim/UX980/UX960NVMe/mulran-radar/KAIST03"

Note, polar_oxford_form folder should be placed in the ${DATA_DIR} directory.

Run script/evaluate_odometry.py as follows:

// E.g.
$ python evaluate_odometry.py -f /media/hyungtaelim/UX960NVMe/mulran/KAIST03/outputs/mulran_ORORA_cen2018_0.6_0.75_0.1_0.15708eval_odom.txt

Acknowledgement

Many thanks to Keenan Burnett to provide outstanding radar odometry codes!

Please refer to Yeti-Radar-Odometry for more information

:mailbox: Contact Information

If you have any questions, please do not hesitate to contact us

Hyungtae Lim :envelope: shapelim at kaist.ac.kr

url-kaist / outlier-robust-radar-odometry

readme