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This paper presents a novel scan matching algorithm which uses not whole scan region but only salient scan region selected around curvature-based features. A curvature function computed by the relative coordinates of neighbor scan points is used to extract salient features which are invariant to translation and rotation. Because the scan matching regions are selected around the salient features, the presented algorithm can be robustly performed even in noisy environments. The robustness of the presented algorithm was tested by datasets obtained from various noisy environments and was verified by consistently showing smaller errors than other scan matching algorithms. Moreover, the presented algorithm was successfully applied to SLAM. [ABSTRACT FROM PUBLISHER]

A scan matching technique is a key technique to implement Cooperative-SLAM (C-SLAM). Although a variety of scan matching techniques have been developed, each of them has both merits and faults. This paper compares and analyzes three well-known scan matching techniques which are ICP (Iterative Closest Points), HSM (Hough Scan Matching), and PSM (Polar Scan Matching). The comparison and analysis are carried out in terms of error and computation time for scan pairs which consists of a reference scan and a current scan. Moreover, the scan matching technique which shows the best performance is applied to C-SLAM. [ABSTRACT FROM PUBLISHER]

This paper presents a survey of map merging techniques for cooperative-SLAM. The recently proposed map merging techniques are classified into two categories: direct map merging and indirect map merging. In each category, several techniques are briefly described. Then, their advantages and disadvantages are discussed in the context of accuracy and computation time. The description and discussion can contribute to realizing and improving cooperative-SLAM. [ABSTRACT FROM PUBLISHER]