Qualitative obstacle detection

Three different algorithms for qualitative obstacle detection are presented in this paper. Each one is based on different assumptions. The first two algorithms are aimed at yes/no obstacle detection without indicating which points are obstacles. They have the advantage of fast determination of the existence of obstacles in a scene based on the solvability of a linear system. The first algorithm uses information about the ground plane, while the second algorithm only assumes that the ground is planar. The third algorithm continuously estimates the ground plane, and based on that determines the height of each matched point in the scene. Experimental results are presented for real and simulated data, and performances of the three algorithms under different noise levels are compared in simulation. We conclude that in terms of the robustness of performance, the third one works best