RIs-Calib: Multi-Radar Multi-IMU Spatiotemporal Calibrator

0. Preliminaries

If you use RIs-Calib in a scientific publication, please cite the following paper 😄:

# todo...

1. Overview

Aided inertial navigation system (INS), typically consisting of an inertial measurement unit (IMU) and an exteroceptive sensor, has been widely accepted and applied as a feasible solution for navigation. Compared with other aided INS, such as vision-aided INS and LiDAR-aided INS, radar-aided INS has better performance in adverse weather conditions such as fog and rain, due to the low-frequency signals radar utilizes. For such a radar-aided INS, accurate spatiotemporal transformation is a fundamental prerequisite to achieving optimal information fusion. In this paper, we present RIs-Calib: a spatiotemporal calibrator for multiple 3D radars and IMUs based on continuous-time estimation, which enables accurate spatial, temporal, and intrinsic calibration, and does not require any additional artificial infrastructure or prior knowledge. Our approach starts with a rigorous and robust procedure for state initialization, followed by batch optimizations, where all parameters can be refined to global optimal states steadily. We validate and evaluate RIs-Calib on both simulated and real-world experiments, and the results demonstrate that RIs-Calib is capable of accurate and consistent calibration. We open-source our implementations at (https://github.com/Unsigned-Long/RIs-Calib) to benefit the research community.

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Demo Video for RIs-Calib

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Our accompanying videos are now available on YouTube (click below images to open) and Bilibili.

2. Build RIs-Calib

2.1 Preparation

• install ROS1 (Ubuntu 20.04 is suggested, Ubuntu 18.04 (ros melodic) is also available):

  sudo apt install ros-noetic-desktop-full
  echo "source /opt/ros/noetic/setup.bash" >> ~/.bashrc
  source ~/.bashrc

  Requirements: ROS1 & C++17 Support

• install Ceres:

  see the GitHub Profile of Ceres library, clone it, compile it, and install it. Make sure that the version of Ceres contains the Manifold module. (Ceres version equal to 2.2.0 or higher than that)

• install Sophus:

  see the GitHub Profile of Sophus library, clone it, compile it, and install it.

• install magic-enum:

  see the GitHub Profile of magic-enum library, clone it, compile it, and install it.

• install Pangolin:

  see the GitHub Profile of Pangolin library, clone it, compile it, and install it.

• install spdlog:

  see the GitHub Profile of spdlog library, clone it, compile it, and install it.

• install fmt, Cereal, spdlog, yaml-cpp:

  sudo apt-get install libfmt-dev
  sudo apt-get install libcereal-dev
  sudo apt-get install libyaml-cpp-dev

2.2 Clone and Compile RIs-Calib

• create a ros workspace if needed and clone RIs-Calib to src directory as ris_calib:

  mkdir -p ~/RIs-Calib/src
  cd ~/RIs-Calib/src
  
  git clone --recursive https://github.com/Unsigned-Long/RIs-Calib.git ris_calib

  change directory to 'ris_calib', and run 'build_thirdparty.sh'.

  cd ris_calib
  chmod +x build_thirdparty.sh
  ./build_thirdparty.sh

  this would build 'tiny-viewer' and 'ctraj' libraries.

• Prepare for thirdparty ros packages:

  clone ros packages 'ainstein_radar', 'ti_mmwave_rospkg', 'serial', 'sbg_ros_driver' to 'ris_calib/..' (directory at the same level as ris_calib):

  cd ..
  git clone https://github.com/AinsteinAI/ainstein_radar.git
  git clone https://github.com/Unsigned-Long/ti_mmwave_rospkg.git
  git clone https://github.com/wjwwood/serial.git
  git clone https://github.com/SBG-Systems/sbg_ros_driver.git

  then change directory to the ros workspace to build these packages:

  cd ..
  catkin_make -DCATKIN_WHITELIST_PACKAGES="ainstein_radar;ti_mmwave_rospkg;serial;sbg_driver"

  Note that these packages will depend on many other ros packages, you need to install them patiently.

• compile RIs-Calib:

  catkin_make -DCATKIN_WHITELIST_PACKAGES=""

3. Launch RIs-Calib

3.1 Simulation Test

simulation experiments (datasets, launch, result visualization)

3.2 Real-world Experiments

real-world experiments (datasets, launch, result visualization)

3.3 Skip Tutorial

Find a configure file named config-real-world.yaml in /ris_calib/config or from the open-source datasets below:

# Google Drive
https://drive.google.com/drive/folders/1_SPdmBnWIJTYyOIkyS0StbPMGVLdV_fw?usp=drive_link

Then change the fields in the configure files to be compatible with your dataset (there are detailed comments for each field). You only need to change a few fields related to io (input and output), perhaps some additional fields related to optimization.

Then give the path of your configuration file to the launch file of RIs-Calib named ris-calib-prog.launch in folder ris_calib/launch, Then, we launch 'RIs-Calib':

roslaunch ris_calib ris-calib-prog.launch

The corresponding results would be output to the directory you set in the configure file.

Attention: Sufficiently excited motion is required for accurate spatiotemporal calibration in RIs-Calib!