A fast and small 3-D Obstacle model for autonomous applications

Abstract

This paper presents a mapping process that can be used for autonomous applications like obstacle avoidance and trajectory planning. The process is real-time capable, and works in full 3-D environments. The mapping starts with building an occupancy grid out of sensor data. Within this grid, single objects are recognized and their polygonal shapes are calculated. The model for object shape representation is rather rough and uses only right prisms and horizontal floor planes. This makes the shape calculation very fast. The extracted objects are not complex so that an external application will be fast as well. As a special application, the approach is tested on an aerial vehicle using a stereo camera system.