Prediction-based geometric feature extraction for 2D laser scanner

This paper presents a novel algorithm for detecting line and circle features from 2D laser range scans. Unlike the conventional methods that use two stages for separating the features: data segmentation and feature separation in each segment, the proposed algorithm adopts a new structure and thus the computation complexity is much reduced. Moreover, it does not depend on prior knowledge of the environment, and it requires a minimum number of points per segment. We utilize prediction to achieve the above goals, so the algorithm is named prediction-based feature extraction (PFE). The efficiency and accuracy of the method is demonstrated by the experiments results.