  Currently, mobile robots are developing rapidly and are finding numerous
applications in industry. However, there remain a number of problems related to
their practical use, such as the need for expensive hardware and their high
power consumption levels. In this study, we propose a navigation system that is
operable on a low-end computer with an RGB-D camera and a mobile robot platform
for the operation of an integrated autonomous driving system. The proposed
system does not require LiDARs or a GPU. Our raw depth image ground
segmentation approach extracts a traversability map for the safe driving of
low-body mobile robots. It is designed to guarantee real-time performance on a
low-cost commercial single board computer with integrated SLAM, global path
planning, and motion planning. Running sensor data processing and other
autonomous driving functions simultaneously, our navigation method performs
rapidly at a refresh rate of 18Hz for control command, whereas other systems
have slower refresh rates. Our method outperforms current state-of-the-art
navigation approaches as shown in 3D simulation tests. In addition, we
demonstrate the applicability of our mobile robot system through successful
autonomous driving in a residential lobby.
