  In this study, we propose a novel visual localization approach to accurately
estimate six degrees of freedom (6-DoF) poses of the robot within the 3D LiDAR
map based on visual data from an RGB camera. The 3D map is obtained utilizing
an advanced LiDAR-based simultaneous localization and mapping (SLAM) algorithm
capable of collecting a precise sparse map. The features extracted from the
camera images are compared with the points of the 3D map, and then the
geometric optimization problem is being solved to achieve precise visual
localization. Our approach allows employing a scout robot equipped with an
expensive LiDAR only once - for mapping of the environment, and multiple
operational robots with only RGB cameras onboard - for performing mission
tasks, with the localization accuracy higher than common camera-based
solutions. The proposed method was tested on the custom dataset collected in
the Skolkovo Institute of Science and Technology (Skoltech). During the process
of assessing the localization accuracy, we managed to achieve centimeter-level
accuracy; the median translation error was as low as 1.3 cm. The precise
positioning achieved with only cameras makes possible the usage of autonomous
mobile robots to solve the most complex tasks that require high localization
accuracy.
