Cluster-based Scan Matching for Robust Motion Estimation and Loop Closing

Abstract

[eng] This paper presents a robust approach to estimate the relative motion between couples of range scans called CSoG. The algorithm first searches prominent structural features in one of the scans by means of a clustering algorithm. Thus, no assumptions about the environment are made. Afterwards, it projects the other scan into the detected feature set and uses a score function to evaluate the projection. By optimizing the score function the motion between the two scans is obtained.Our approach is compared to two well known scan matchers using real data from three different sensors: a terrestrial sonar, a terrestrial laser and an underwater sonar. Results show a significant improvement of CSoG with respect to the other algorithms in the case of medium and large motions between the scans. Accordingly, CSoG is a good choice to perform dead reckoning from range data and to close large loops in SLAM.