rio

Graph-based, sparse radar-inertial odometry m-estimation with barometer support and zero-velocity tracking.

Paper: https://arxiv.org/pdf/2408.05764

@inproceedings{girod2024brio,
author = {Rik Girod and Marco Hauswirth and Patrick Pfreundschuh and Mariano Biasio and Roland Siegwart},
title = {A robust baro-radar-inertial odometry m-estimator for multicopter navigation in cities and forests},
booktitle={IEEE Int. Conf. Multisensor Fusion Integration Intell. Syst.},
year={2024}
}

Installation

Install ROS noetic.

sudo apt install git build-essential python3-rosdep python3-catkin-tools ros-noetic-rqt-multiplot -y
mkdir catkin_ws
cd catkin_ws
mkdir src
catkin init
cd src
git clone https://github.com/ethz-asl/rio.git
git clone https://github.com/ethz-asl/lpp.git
git clone https://github.com/rikba/gtsam_catkin.git
cd ..
rosdep install --from-paths src --ignore-src -r -y
catkin build

Launch

Start RIO in one terminal

source ~/catkin_ws/devel/setup.bash
roslaunch rio rio.launch visualize:=true

Download an example dataset sequence.

Replay the bag

rosbag play 01_urban_night_H_raw.bag

Supported sensors

Sensor	Default topic	Message type	Required	Note
IMU	/imu/data_raw	sensor_msgs/Imu	Yes	Calibrate gyro turn-on-bias!
IMU filtered	/imu/data	sensor_msgs/Imu	Yes	for initialization
Radar	/radar/cfar_detections	sensor_msgs/PointCloud2	Yes
Barometer	/baro/pressure	sensor_msgs/FluidPressure	No	Activate in cfg

Radar point cloud format, see also mav_sensors_ros.

| Field name | Size    |
| ---------- | ------- |
| x          | FLOAT32 |
| y          | FLOAT32 |
| z          | FLOAT32 |
| doppler    | FLOAT32 |
| snr        | INT16   |
| noise      | INT16   |

Dataset

The dataset contains 15 sequences of urban night, forest path, field, and deep forest handheld and flown data. It can be downloaded with and without camera images.

dataset_quadrotor_examples.mp4

Scenario	No.	Link w/o camera
Urban Night	01	01_urban_night_H_raw_no_img.bag
	02	02_urban_night_H_raw_no_img.bag
	03	03_urban_night_H_raw_no_img.bag
	04	04_urban_night_H_raw_no_img.bag
	05	05_urban_night_F_raw_no_img.bag
	06	06_urban_night_F_raw_no_img.bag
	07	07_urban_night_F_raw_no_img.bag
Forest Path	08	08_forest_path_H_raw_no_img.bag
	09	09_forest_path_H_raw_no_img.bag
	10	10_forest_path_H_raw_no_img.bag
	11	11_forest_path_F_raw_no_img.bag
	12	12_forest_path_F_raw_no_img.bag
Flat Field	13	13_flat_field_F_raw_no_img.bag
	14	14_flat_field_F_raw_no_img.bag
Tree Slalom	15	15_tree_slalom_F_raw_no_img.bag

All	01-15	all_raw_no_img

Calibration

| Field name | IMU to radar | radar to cam |
| ---------- | ------------ | ------------ |
| x          | 0.122        | -0.020       |
| y          | 0.000        | -0.015       |
| z          | -0.025       | 0.000        |
| qx         | 0.67620958   | 0.000        |
| qy         | 0.67620958   | 0.7071068    |
| qz         | -0.20673802  | 0.7071068    |
| qw         | -0.20673802  | 0.000        |

<node name="imu_to_radar_broadcaster" pkg="tf2_ros" type="static_transform_publisher" args="0.122 0.000 -0.025 0.67620958 0.67620958 -0.20673802 -0.20673802 'bmi088' 'awr1843aop'" />
<node name="radar_to_cam_broadcaster" pkg="tf2_ros" type="static_transform_publisher" args="-0.020 -0.015 0.0 0.0 0.7071068 0.7071068 0.0 'awr1843aop' 'cam'" />

Related packages

Package	Description	Link
mav_sensors	Linux user space sensor drivers	mav_sensors
mav_sensors_ros	ROS sensor interface	mav_sensors_ros