Awesome Open Source
Awesome Open Source


ROS Wrapper for Kimera.


We kindly ask to cite our paper if you find this library useful:

  title = {Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping},
  author = {Rosinol, Antoni and Abate, Marcus and Chang, Yun and Carlone, Luca},
  year = {2020},
  booktitle = {IEEE Intl. Conf. on Robotics and Automation (ICRA)},
  url = {},
  pdf = {}

1. Installation

A. Prerequisities

sudo apt-get install ros-melodic-image-geometry ros-melodic-pcl-ros ros-melodic-cv-bridge
  • System dependencies: First, update package list: sudo apt-get update
sudo apt-get install -y --no-install-recommends apt-utils
sudo apt-get install -y \
      cmake build-essential unzip pkg-config autoconf \
      libboost-all-dev \
      libjpeg-dev libpng-dev libtiff-dev \
# Use libvtk5-dev, libgtk2.0-dev in ubuntu 16.04 \
      libvtk6-dev libgtk-3-dev \
      libatlas-base-dev gfortran \
      libparmetis-dev \
      python-wstool python-catkin-tools \

B. KimeraVIO ROS wrapper Installation

# Setup catkin workspace
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/
catkin init
# On Ubuntu 16.04:

catkin config --merge-devel

# Add workspace to bashrc for automatic sourcing of workspace.
echo 'source ~/catkin_ws/devel/setup.bash' >> ~/.bashrc

# Clone repo
cd ~/catkin_ws/src
# For ssh:
git clone [email protected]:MIT-SPARK/Kimera-VIO-ROS.git
# For https:
# git clone

# Install dependencies from rosinstall file using wstool
wstool init # Use unless wstool is already initialized

# For ssh:
wstool merge Kimera-VIO-ROS/install/kimera_vio_ros_ssh.rosinstall
# For https
# wstool merge Kimera-VIO-ROS/install/kimera_vio_ros_https.rosinstall

# download and update repos:
wstool update

# Optionally install all dependencies that you might have missed:
# Some packages may report errors, this is expected
# rosdep install --from-paths . --ignore-src -r -y

Finally, compile:

# Compile code
catkin build

# Refresh workspace
source ~/catkin_ws/devel/setup.bash

2. Usage

Download a Euroc rosbag: for example V1_01_easy.


  1. As a general good practice, open a new terminal and run: roscore

  2. In another terminal, launch KimeraVIO ROS wrapper:

roslaunch kimera_vio_ros kimera_vio_ros_euroc.launch
  1. In another terminal, launch rviz for visualization:
rviz -d $(rospack find kimera_vio_ros)/rviz/kimera_vio_euroc.rviz

Note: this rviz configuration makes use of a rviz plugin: mesh_rviz_plugins. To visualize the textured 3D mesh, clone this plugin to your catkin workspace and catkin build it (note that this should be done automatically via wstool).

  1. Finally, in another terminal, launch the downloaded Euroc rosbag:
rosbag play --clock /PATH/TO/EUROC_ROSBAG

Note that you will need to both source ROS and your catkin_ws for each new terminal unless you added the following lines to your ~/.bashrc file:

source /opt/ros/melodic/setup.bash  # Change `melodic` for your ROS distribution.
source ~/catkin_ws/devel/setup.bash # Change `bash` to the shell you use.


In this mode, the provided rosbag will be first parsed and then sent to the VIO for processing. This is particularly useful when debugging to avoid potential ROS networking issues.

  • To run, launch the KimeraVIO ROS wrapper with the online parameter set to false and specify the rosbag's path:
roslaunch kimera_vio_ros kimera_vio_ros_euroc.launch online:=false rosbag_path:="PATH/TO/ROSBAG"

Running Unit tests

To run unit tests using catkin for this specific package, call (after building the package and sourcing the workspace):

catkin run_tests --no-deps --this

Other functionalities

Using camera_info topics instead of Yaml parameters

It is sometimes convenient to use the camera_info topics to parse the camera's parameters. There are currently two ways of using these topics:

  • Offline: using the launch file launch/cam_info_yamlizer.launch which will generate yaml files out of the topics. You need to make sure that the frame_ids and the ROS topics are correctly set. Also, mind that the left/right cam frame ids are typically set as static tfs in a rosbag, therefore, first launch the node, and then run the rosbag (in case you see an exception bcs of a missing frame_id).
  • Online: setting the flag use_online_cam_params (see launch/kimera_vio_ros.launch) to true, and ensuring ROS topics are correctly set.

Restart Kimera-VIO

The typical use case is that you have multiple rosbags and you don't want to be killing Kimera-VIO(-ROS) each time. If this is your case, then we provide a rosservice to restart Kimera-VIO (it will do a hard restart, meaning the whole pipeline and data provider will be destructed and constructed again).

rosservice call /kimera_vio_ros/kimera_vio_ros_node/restart_kimera_vio

Note that Kimera-VIO will complain if timestamps are not strictly increasing. Therefore, one must follow these steps:

  1. Start Kimera-VIO and rosbag
  2. Stop rosbag
  3. Call rosservice to restart VIO
  4. Start another rosbag

Enable Dense Depth Stereo estimation

This will run OpenCV's StereoBM algorithm, more info can be found here (also checkout this to choose good parameters):

roslaunch kimera_vio_ros kimera_vio_ros_euroc run_stereo_dense:=1

This will publish a /stereo_gray/points2 topic, which you can visualize in Rviz as a 3D pointcloud. Alternatively, if you want to visualize the depth image, since Rviz does not provide a plugin to visualize a disparity image, we also run a disparity_image_proc nodelet that will publish the depth image to /stereo_gray/disparity_image_proc/depth/image_raw.

Hardware use

See the documentation on hardware setup for instructions on running KimeraROS on supported hardware platforms, as well as guides on how to develop for other platforms.

BSD License

KimeraVIO ROS wrapper is open source under the BSD license, see the LICENSE.BSD file.

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