Real-time 2D height mapping method for an unmanned vehicle using a stereo camera and laser sensor fusion

This paper proposes a method for mapping the height information on an area around a vehicle and of identifying a drivable area by fusing a stereo camera and a laser sensor. A SOM (Self Organizing Map) clustering algorithm obtained from the depth information of the stereo camera is used to analyze the front part area of a vehicle in forms of several candidate planes. In addition, an IMU indicating the current pose of a vehicle is applied to detect a drivable plane. A laser sensor installed on a vehicle’s roof scans the front part with a single line and informs a distance value. A drivable plane detected is utilized to calculate height value in the normal direction detected by the laser scan data. Additionally, when the height already mapped has a value higher than that of the threshold, it is regarded as an obstacle and the vehicle is prevented from coming into contact with it. Regarding the vehicle position estimation, a Kalman filter method is used for real-time mapping during driving. The moving location of the vehicle is dead reckoned based on steering angle and velocity, and this value is compensated using the position value received from the GPS. The vehicle’s position and mapping coordinates are converted into latitude and longitude values. This study demonstrates that it is possible to generate a precise 2D height map by conducting a test in a real road environment with various slope angles and obstacles.