Laser Scanner Obstacle Recognition via Layered Data Segmentation

The patent segments the laser scanner data into multiple layers based on altitude information. By dividing the data into distinct layers (e.g., ground layer, vehicle layer, pedestrian layer), the system can separate obstacles from background noise more effectively. This segmentation allows accurate identification of different obstacle types without relying solely on angle and distance information, thereby improving data separation accuracy while maintaining obstacle detection capability.

The patent applies local quality by analyzing the altitude information of each laser scanner data point to determine its semantic meaning. Different altitude ranges are assigned different interpretations: lower altitudes correspond to ground, intermediate altitudes to vehicles, and higher altitudes to pedestrians. This localized interpretation based on altitude enables the system to distinguish between actual obstacles and noise (ground reflections) while maintaining extensive detection range, thereby reducing false positives.

The patent makes the laser scanner multi-functional by enabling it to perform not only traditional obstacle detection but also altitude-based classification of obstacles (ground, vehicle, pedestrian). By extracting and utilizing altitude information from the laser scanner data, the system achieves enhanced recognition accuracy without requiring additional sensors. This multi-functionality approach improves recognition accuracy while avoiding the complexity increase that would result from integrating multiple separate sensors.