Mathias Haberjahn

Vehicle environment detection by a combined low and mid level fusion of a laser scanner and stereo vision

A sensor system consisting of a multi layer laser scanner and a stereo camera is used to observe the surrounding environment of a vehicle. By a novel multi level fusion framework the heterogeneous sensor data can be merged on different processing levels. The following paper gives a short introduction to the processing steps of the sensor data and focuses on the lower raw level and middle object level fusion. Here, the low level fusion obtains a more precise object discrimination, whereas the mid level fusion is able to solve conflicting sensor statements with competing object information. A combination of both, obviously results in a more accurate environmental description. The effectiveness of both fusion approaches is tested and compared with real road reference data, obtained from highly precise GPS data.

Object discrimination and tracking in the surroundings of a vehicle by a combined laser scanner stereo system

The use of sensor data for observing the surrounding environment of a vehicle is becoming increasingly popular. Especially for detecting dangerous situations, which occur too fast for the human senses, sensor systems are needed. In the following paper such a sensor system consisting of a stereo camera and a multilayer laser scanner mounted in front of a test vehicle is introduced. Both sensors are used to detect and track obstacles and other traffic objects independent from each other for future data fusion. An overview of the complete process for the object discrimination including a novel approach for a sensor cross calibration and a new method for the object refinement and the object tracking is given. The effectiveness of the algorithms are tested with real road reference data, obtained through highly precise GPS data.