# Lane Detection Algorithm Using LRF for Autonomous Navigation of Mobile Robot
## 2 System Structure  
Figure 1 shows the configuration of the mobile robot system. This system is mainly divided into a mobile robot platform and a data control platform. The upper part of the dashed line represents the mobile platform, and the lower part, the data control platform. The mobile platform is subdivided into sensor and motor controller units, on the left and right sides of Figure 1, respectively. The sensor unit of the mobile platform is composed of the LRF, inertial measurement unit (IMU), and encoder as well as the sensor controller. Sensors measure the information necessary for building road maps and controlling the robot, and the data controller receives the data values obtained by the sensors and ensures a stable transfer to the data control platform. LRF is used for obtaining the road information by scanning the road using a laser. The IMU sensor is used for obtaining information on the position and direction of the robot. The encoder is used for measuring the rotational values of the mobile robot's motor and obtaining the information on distance covered and relative coordinates by means of dead reckoning. The motor control unit of the mobile platform is composed of the motor drive, motor, and motor controller. The motor controller interprets the control signals received from the data control platform in order for the mobile robot to navigate stably and the motor drive for moving the mobile robot according to the instructions from the motor controller. The data control platform consists of a personal computer (PC)-based program and executes functions such as creation of 3D road maps with the data transferred from the mobile platform sensor unit, extraction of lane feature points, prediction of lanes, and generation of control signals. Further, it transfers the generated control signals to the mobile platform motor control unit for the mobile robot to navigate stably along the lane. Figure 2 shows the structure of the robot built for this study. The LRF on the right-hand side is a sensor used for obtaining road information. The sensors produced by Hokuyo Ltd. and Sick AG are mostly widely used, and the URG-04 LX of the Hokuyo Ltd. used in this study has a relatively narrow measurement range compared to the sensor by Sick AG, but  
Figure 1: System configuration. its minimum measurement distance is very close and its resolution makes it suitable for building 3D maps and scanning lanes. The IMU positioned at the upper end is a module composed of an accelerator, gyro, and compass sensors, and is used for measuring the direction and position of the robot. Since it is considerably influenced by iron or a magnet, a sufficient distance should separate it from the robot's main body, motor, and the other parts. The micro controller unit (MCU) placed at the bottom part is a sensor controller sending data to the PC and a motor controller that transfers the instructions received from the PC to the motor drive. These two controllers and the motor drive are positioned at the center. The components used in the experiment are listed in Tables 1-4. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Light Source** & Semiconductor laser diode (785 nm) \\  & & Laser safety Class1 (IEC60825-1) \\ \hline  & **Detection Distance** & Accuracy Range: 60–4095 mm \\  & **Standard Object** & Square Kent Sheet 80 mm \\ \hline  & **Detection Distance** & \\  & **/Scan Angle** & 20–4000 mm/240\({}^{\circ}\) \\ \hline  & **Resolution/** & 1 mm/0.36\({}^{\circ}\)(360\({}^{\circ}\)/1024 steps) \\ \hline  & **Scan Time** & 100 msec/scan \\ \hline  & **Interface** & RS-232C (19.2, 57.6, 115.2, 500, 750 kbps) \\  & & USB 2.0 (Full Speed) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Laser range finder: UBG-04 LX.