A VI SLAM system that integrates IMU neural network observations, developed based on vins-mono.
IMU neural network using RNIN-VIO,the pretrained-model can be downloaded from:model(password:gwkw).
Because neural networks are suitable for handheld devices, we provide a data packet collected by iphone12,sample data can be downloaded from Rosbag(password ovci)
1.1 ROS ROS Installation
sudo apt-get install ros-YOUR_DISTRO-cv-bridge ros-YOUR_DISTRO-tf ros-YOUR_DISTRO-message-filters ros-YOUR_DISTRO-image-transport
we use libtorch1.8.2+cu102 for nural network inference.
1.2. Ceres Solver Follow Ceres Installation, remember to make install. (Our testing environment: Ubuntu 18.04, ROS Melodic, OpenCV 4.5, Eigen 3.3.3)
Clone the repository and catkin_make:
catkin_make
source ~/catkin_ws/devel/setup.bash
roslaunch vins_estimator euroc.launch
roslaunch vins_estimator vins_rviz.launch
rosbag play YOUR_PATH_TO_DATASET/MH_01_easy.bag
[1]Chen D, Wang N, Xu R, et al. Rnin-vio: Robust neural inertial navigation aided visual-inertial odometry in challenging scenes[C]//2021 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2021: 275-283.
[2]Qin T, Li P, Shen S. Vins-mono: A robust and versatile monocular visual-inertial state estimator[J]. IEEE Transactions on Robotics, 2018, 34(4): 1004-1020.