| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 719771 | IFAC Proceedings Volumes | 2007 | 6 Pages |
Collision avoidance is one of the most important capabilities for autonomous vehicles. During driving, collisions must be avoided in all situations. With the availability of 3d cameras which rely on the time-of-flight principle, it is possible to get a very rich perception of the environment. This paper shows, how obstacles can be detected in the vehicle's surrounding using a 3d PMD-camera (photonic mixing device). The obstacle detection is composed of two separated steps. First, a segmentation and a clustering of pixels takes place. Secondly, each group of pixels is analyzed in order to decide whether it is an obstacle or not. The result of the detection is a list of obstacles which is then used for behavior execution. The execution is done with a behavior network and it generates recommendations for path planning.
