Vision-based approach to obstacle avoidance

This paper describes a 3D obstacle modeling system which uses a 2D vision sensor. Prior work tracks feature points in a sequence of images and estimates their positions. However, in this paper we use obstacle edges instead. Using an image segmentation technique, edges are detected as line segments. Subsequently, these edges are modeled in a 3D space from the measured line segments using known camera motions. The z-test method is used for corresponding estimated line data with measurements. Line addition and deletion algorithms are also explained. Simulation results show that simple structures are accurately modeled by the suggested line-based estimator. Finally, this method is applied to a 3D terrain mapping problem.