MINS

An efficient, robust, and tightly-coupled Multisensor-aided Inertial Navigation System (MINS) which is capable of flexibly fusing all five sensing modalities (IMU, wheel encoders, camera, GNSS, and LiDAR) in a filtering fashion by overcoming the hurdles of computational complexity, sensor asynchronicity, and intra-sensor calibration.

Exemplary use case of MINS:

• VINS (mono, stereo, multi-cam)
• GPS-IMU (single, multiple)
• LiDAR-IMU (single, multiple)
• wheel-IMU
• Camera-GPS-LiDAR-wheel-IMU or more combinations.

• Publication reference - https://arxiv.org/pdf/2309.15390.pdf

Key Features

• Inertial(IMU)-based multi-sensor fusion including wheel odometry and arbitrary numbers of cameras, LiDARs, and GNSSs (+ VICON or loop-closure) for localization.
• Online calibration of all onboard sensors (check exemplary results).
• Consistent high-order state on manifold interpolation improved from our prior work (MIMC-VINS) and dynamic cloning strategy for light-weight estimation performance.
• Multi-sensor simulation toolbox for IMU, camera, LiDAR, GNSS, and wheel enhanced from our prior work (OpenVINS)
• Evaluation toolbox for consistency, accuracy, and timing analysis.
• Very detailed options for each sensor enabling general multi-sensor application.

Dependency

MINS is tested on Ubuntu 18 and 20 and only requires corresponding ROS (Melodic and Noetic).

• Default Eigen version will be 3.3.7 (Noetic) or lower, but if one has a higher version the compilation can be failed due to thirdparty library (libpointmatcher) for LiDAR.

Build and Source

mkdir -p $MINS_WORKSPACE/catkin_ws/src/ && cd $MINS_WORKSPACE/catkin_ws/src/
git clone https://github.com/rpng/MINS
cd .. && catkin build
source devel/setup.bash

Run Examples

Simulation

roslaunch mins simulation.launch cam_enabled:=true lidar_enabled:=true

Real-World Dataset

Directly reading the ros bag file

roslaunch mins rosbag.launch config:=kaist/kaist_LC path_gt:=urban30.txt path_bag:=urban30.bag

Here are the rosbag files and ground truths we used in the evaluation. To be specific, we used kaist2bag to convert all sensor readings to rosbag files. All rights reserved to KAIST urban dataset. | Rosbag | GT (csv) | GT (txt) | Rosbag | GT (csv) | GT (txt) | | --- | --- | --- | --- | --- | --- | |urban18.bag|urban18.csv|urban18.txt|urban19.bag|urban19.csv|urban19.txt| |urban20.bag|urban20.csv|urban20.txt|urban21.bag|urban21.csv|urban21.txt| |urban22.bag|urban22.csv|urban22.txt|urban23.bag|urban23.csv|urban23.txt| |urban24.bag|urban24.csv|urban24.txt|urban25.bag|urban25.csv|urban25.txt| |urban26.bag|urban26.csv|urban26.txt|urban27.bag|urban27.csv|urban27.txt| |urban28.bag|urban28.csv|urban28.txt|urban29.bag|urban29.csv|urban29.txt| |urban30.bag|urban30.csv|urban30.txt|urban31.bag|urban31.csv|urban31.txt| |urban32.bag|urban32.csv|urban32.txt|urban33.bag|urban33.csv|urban33.txt| |urban34.bag|urban34.csv|urban34.txt|urban35.bag|urban35.csv|urban35.txt| |urban36.bag|urban36.csv|urban36.txt|urban37.bag|urban37.csv|urban37.txt| |urban38.bag|urban38.csv|urban38.txt|urban39.bag|urban39.csv|urban39.txt|

Subscribing to the ros messages

roslaunch mins subscribe.launch config:=euroc_mav rosbag:=V1_03_difficult.bag bag_start_time:=0

RViz

rviz -d mins/launch/display.rviz

Acknowledgements

This project was built on top of the following libraries which are in the thirdparty folder.

• OpenVINS: Open-source filter-based visual-inertial estimator.
• [ikd-tree](https://github.com/hk