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VIDO-SLAM is a Visual-Inertial Dynamic Object SLAM System that is able to estimate the camera poses, perform Visual, Visual-Inertial SLAM with monocular camera, track dynamic objects. We provide demo to run the SLAM system in the Kaist Dataset using monocular camera, with or without IMU.

This software is based onVDO-SLAM ,FlowNet,Mask RCNN.MonoDepth2,ORB_SLAM3

Features:

• Integrate MonoDepth2, FlowNet and MaskRcnn with ROS that can run in SLAM system in real time
• Visual-Inertial SLAM in real-world outdoor scenarios
• Track and Estimate dynamic objects motion

• Jun Zhang, Mina Henein, Robert Mahony and Viorela Ila.VDO-SLAM: A Visual Dynamic Object-aware SLAM System. Submitted to The International Journal of Robotics Research.IJRR (Under Review).
• Carlos Campos, J. M. M. Montiel and Juan D. Tardós,Inertial-Only Optimization for Visual-Inertial Initialization,ICRA 2020.

• ROS
• PyTorch (Version: 1.4.0)
• GPU (at least 8GB of memory)
• OpenCV
• Pangolin
• g2o
• Eigen

Clone the repository:

https://github.com/bxh1/VIDO-SLAM.git

The directory structure is as follows

VIDO-SLAM   ├── README.md   ├── src   ├── figure   └── vido_slam

VIDO-SLAM/src/thirdparty/mask_rcnn must be build withpython3 install.py install. This builds and installs the CUDA files needed by this network.

VIDO-SLAM/vido_slam must be build with cmake:

mkdir buildcd build && cmake .. && make -j4

A dynamic library will be built in this folder: vido_slam/lib/libvido_slam.so

VIDO-SLAM/src/thirdparty andVIDO-SLAM/src/realtime_demo are ROS package, build with catkin_make

cd VIDO-SLAMcatkin_make

VIDO-SLAM has two modes: offline and online.

Offline mode needs to run three networks in advance to get data, and then run the following command:

cd VIDO-SLAM/vido_slam/build./run_vido  path_to_VIDO-SLAM/src/config/kaist_config.yaml

Online mode runs three networks in real time through ROS, and sends the network results into vido-slam system:

cd VIDO-SLAMsource devel/setup.bashroslaunch demo run_realtime_vido.launch

The VO and VIO switch options are in the config file:

Visual-Inertial optimization