The likelihood field approach to sonar scan matching

In this paper, a new method to perform scan matching using sparse sets of noisy readings is presented and tested with sonar sensors. This method, the LF/SoG, does not rely on the establishment of correspondences. The underlying idea is to model one of the scans by a function of x-y-coordinates, the Likelihood Field, depicting the likelihood of obstacle detection. Then, the scan matching problem turns into an optimization problem involving the Likelihood Field and the other scan. Because no correspondences are established, the main problems of ICP-based algorithms are not present in the LF/SoG. The presented experimental results validate the LF/SoG approach and compare it with other well known scan matching algorithms in terms of robustness, accuracy and convergence rate.