Skip to content

Continuous-time lidar, radar, lidar-inertial, and radar-inertial odometry

License

Notifications You must be signed in to change notification settings

utiasASRL/steam_icp

Repository files navigation

STEAM-ICP

Paper: IMU as an Input vs. a Measurement of the State in Inertial-Aided State Estimation

In this paper, we implemented lidar-inertial odometry using a Singer prior where body-centric acceleration is included in the state. In the paper, we refer to this as our Singer prior lidar(-inertial) odometry which can be configured to be lidar-only, lidar + gyro, or lidar-inertial using both accelerometer and gyroscope. This is implemented in steam_icp/src/odometry/steam_lio.cpp where use_imu=True in the configuration yaml enables the use of an IMU.

Paper: Continuous-Time Radar-Inertial and Lidar-Inertial Odometry using a Gaussian Process Motion Prior

In the paper, we implemented radar-inertial and lidar-inertial odometry using a white-noise-on-acceleration prior where accelerometer measurements are preintegrated to form relative velocity factors. We compare several variants of our approach such as lidar-only: STEAM-LO, lidar-inertial: STEAM-LIO, radar-only: STEAM-RO, and radar-inertial: STEAM-RIO. STEAM-LO and STEAM-LIO are implemented in steam_icp/src/odometry/steam_lo.cpp where use_imu=True in the configuration yaml enables the use of an IMU. Similarly, STEAM-RO and STEAM-RIO are implemented in steam_icp/odometry/steam_ro.cpp.

To be clear, the algorithms associated with the "continuous-time radar-inertial ..." are implemented in steam_lo.cpp and steam_ro.cpp which use the white-noise-on-acceleration prior. The algorithms associated with the "imu as input ..." paper are implemented in steam_lio.cpp which uses a Singer prior.

Previous Paper: Picking Up Speed: Continuous-Time Lidar-Only Odometry using Doppler Velocity Measurements

In our previous work, we demonstrate continuous-time lidar odometry which incorporated Doppler velocity measurements from an Aeva lidar. For code that pertains to the picking-up-speed paper, git checkout picking_up_speed

Datasets: Boreas (ours) and KITTI-raw/360 (made available by the authors of CT-ICP) and Aeva (a collaboration between us and Aeva) and Newer College Dataset

Installation

Clone this repository and its submodules.

We use docker to install dependencies The recommended way to build the docker image is

docker build -t steam_icp \
  --build-arg USERID=$(id -u) \
  --build-arg GROUPID=$(id -g) \
  --build-arg USERNAME=$(whoami) \
  --build-arg HOMEDIR=${HOME} .

When starting a container, remember to mount the code, dataset, and output directories to proper locations in the container. An example command to start a docker container with the image is

docker run -it --name steam_icp \
  --privileged \
  --network=host \
  -e DISPLAY=$DISPLAY \
  -v /tmp/.X11-unix:/tmp/.X11-unix \
  -v ${HOME}:${HOME}:rw \
  steam_icp

(Inside Container) Go to the root directory of this repository and build STEAM-ICP

bash build.sh

Experiments

Commands below should be run in the docker container.

# set to the root directory of this repository
WORKING_DIR=$(pwd)

# add library paths
EXTERNAL_ROOT=${WORKING_DIR}/cmake-build-Release/external/install/Release
LGMATH_ROOT=${WORKING_DIR}/cmake-build-Release/lgmath/install/Release
STEAM_ROOT=${WORKING_DIR}/cmake-build-Release/steam/install/Release
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${EXTERNAL_ROOT}/Ceres/lib:${EXTERNAL_ROOT}/glog/lib
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${LGMATH_ROOT}/lib:${STEAM_ROOT}/lib

# run experiments - configure algorithm and dataset in the params file
source ${WORKING_DIR}/steam_icp/install/setup.bash
# this would run STEAM-ICP from our "picking up speed" paper
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/default_config.yaml
# this would run STEAM-LIO from our "continuous-time radar-inertial..." paper (on the Boreas dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_velodyne_steamlio_config.yaml
# this would run STEAM-LO from our "continuous-time radar-inertial..." paper (on the Boreas dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_velodyne_steamlo_config.yaml
# this would run STEAM-RIO from our "continuous-time radar-inertial..." paper (on the Boreas dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_navtech_paper_results_config.yaml
# after setting use_imu=False in the yaml file, this would run STEAM-RO from our "continuous-time radar-inertial..." paper (on the Boreas dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_navtech_paper_results_config.yaml
# this would run STEAM-RIO++ from our "continuous-time radar-inertial..." paper (on the Boreas dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_navtech_steamro_config.yaml
# this would run STEAM-LO from our "continuous-time radar-inertial..." paper (on the KITTI-raw dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/kitti_raw_steamlo_config.yaml
# this would run STEAM-LIO from our "continuous-time radar-inertial..." paper (on the KITTI-raw dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/kitti_raw_steamlio_config.yaml
# this would run STEAM-LO from our "continuous-time radar-inertial..." paper (on the Newer College dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_steamlo_config.yaml
# after setting use_imu=True, use_accel=True, qc_diag = [500., 500., 500., 50., 50., 50.] in the yaml file, this would run STEAM-LIO from our "continuous-time radar-inertial..." paper (on the Newer College dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_steamlo_config.yaml
# after setting use_imu=True, use_accel=False, qc_diag = [500., 500., 500., 50., 50., 50.] in the yaml file, this would run STEAM-LO+Gyro from our "continuous-time radar-inertial..." paper (on the Newer College dataset)
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_steamlo_config.yaml

### IMU as input vs. as measurement paper:
# To run the Singer prior as lidar-inertial odometry on a simulated dataset
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_simulation_singer_config.yaml
# after setting use_accel=False, this would run Singer prior as lidar + Gyro only on a simulated dataset
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_simulation_singer_config.yaml
# after setting use_imu=False, qc_diag=[5000.,5000.,5000.,500.,500.,500.], this would run Singer prior as lidar-only on a simulated dataset
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/boreas_simulation_singer_config.yaml
# To run the Singer prior as lidar-inertial odometry on the Newer College dataset
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_singer_config.yaml
# after setting use_accel=False, to run the Singer prior as lidar + gyro only on the Newer College dataset
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_singer_config.yaml
# after setting use_imu=False, ad_diag = [100.0,100.0,100.0,100.,100.,100.], qc_diag = [500000.,500000.,500000.,50000.,50000.,50000.], use_line_search=False, to run the Singer prior as lidar-only odometry on the Newer College Dataset, use:
ros2 run steam_icp steam_icp --ros-args --params-file ${WORKING_DIR}/steam_icp/config/ncd_singer_config.yaml


# (optional) rviz for visualization - run following commands in another terminal
source /opt/ros/galactic/setup.bash
ros2 run rviz2 rviz2 -d ${WORKING_DIR}/steam_icp/rviz/steam_icp.rviz # launch rviz

Running the lidar-inertial simulation:

ros2 run steam_icp simulation --ros-args --params-file ${WORKING_DIR}/steam_icp/simulation/sim.yaml

Note that some of the code for generating maps and plots for the "continuous-time radar-inertial..." paper is located on the map_and_plots branch.

In terms of outputs, you should get something similar to the files in the results directory.

Evaluation

See python scripts in the script directory for evaluation.

The following papers are based on this repository and can be cited as follows:

@ARTICLE{wu_ral23,
  author={Wu, Yuchen and Yoon, David J. and Burnett, Keenan and Kammel, Soeren and Chen, Yi and Vhavle, Heethesh and Barfoot, Timothy D.},
  journal={IEEE Robotics and Automation Letters}, 
  title={Picking up Speed: Continuous-Time Lidar-Only Odometry Using Doppler Velocity Measurements}, 
  year={2023},
  volume={8},
  number={1},
  pages={264-271},
  doi={10.1109/LRA.2022.3226068}
}
@article{burnett_arxiv24,
  title={Continuous-Time Radar-Inertial and Lidar-Inertial Odometry using a Gaussian Process Motion Prior},
  author={Burnett, Keenan and Schoellig, Angela P and Barfoot, Timothy D},
  journal={arXiv preprint arXiv:2402.06174},
  year={2024}
}
@article{burnett_arxiv24b,
  title={IMU as an Input vs. a Measurement of the State in Inertial-Aided State Estimation},
  author={Burnett, Keenan and Schoellig, Angela P and Barfoot, Timothy D},
  journal={arXiv preprint arXiv:2403.05968},
  year={2024}
}

About

Continuous-time lidar, radar, lidar-inertial, and radar-inertial odometry

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published