  Exploration of an unknown environment by a mobile robot is a complex task
involving solution of many fundamental problems from data processing,
localization to high-level planning and decision making. The exploration
framework we developed is based on processing of RGBD data provided by a MS
Kinect2 sensor, which allows to take advantage of state-of-the-art SLAM
(Simultaneous Localization and Mapping) algorithms and to autonomously build a
realistic 3D map of the environment with projected visual information about the
scene. In this paper, we describe practical issues that appeared during
deployment of the framework in real indoor and outdoor environments and discuss
especially properties of SLAM algorithms processing MS Kinect2 data on an
embedded computer.
