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Abstract
The paper presents Perimeter-Based Polar Scan Matching (PB-PSM), a new 2D scan matching algorithm. The algorithm favors matches with a larger perimeter overlap between the two input scans, while using a robust cost minimization process (using an adaptive direct search method, made possible due to a linear complexity data association technique). PB-PSM is benchmarked against the previously published PSM and PSM-C algorithms, and numerous realizations of the ICP algorithm. Results for convergence, accuracy, and computational speed are discussed. PB-PSM is employed on several laser scan datasets, both existing and in-house. Quantitative comparison of resulting maps is done using a new metric for evaluating occupancy grid maps accuracy, by calculating the average cell distance from the walls of the true map. The relative importance of each novel contribution is quantified using the new metric. Additional qualitative analysis is provided for previously published and relatively large datasets.