  In this paper, we present our software sensor fusion framework for
self-driving cars and other autonomous robots. We have designed our framework
as a universal and scalable platform for building up a robust 3D model of the
agent's surrounding environment by fusing a wide range of various sensors into
the data model that we can use as a basement for the decision making and
planning algorithms. Our software currently covers the data fusion of the RGB
and thermal cameras, 3D LiDARs, 3D IMU, and a GNSS positioning. The framework
covers a complete pipeline from data loading, filtering, preprocessing,
environment model construction, visualization, and data storage. The
architecture allows the community to modify the existing setup or to extend our
solution with new ideas. The entire software is fully compatible with ROS
(Robotic Operation System), which allows the framework to cooperate with other
ROS-based software. The source codes are fully available as an open-source
under the MIT license. See https://github.com/Robotics-BUT/Atlas-Fusion.
