SLAM-ICP with a Boolean method applied on a car-like robot

Scan matching is a popular way of recovering a mobile robot's motion and constitutes the basis of many localization and mapping approaches. Consequently, a variety of scan matching algorithms have been proposed in the past. All these algorithms share one common attribute: They match pairs of scans to obtain spatial relations between two robot poses. The work presented in this paper consists in the implementation of a SLAM algorithm (Simultaneous Localization and Mapping) on a car-like vehicle. Our algorithm is based on a measurement alignment method called “Iterative Closest Points” (ICP) using binary weighted method (Boolean). It helps find the rigid transformation that minimizes the distance between two clouds of points. The developed algorithm (SLAM-ICP) has been implemented and tested on the mobile robot. Experimental results given at the end of this paper are compared to classical localization technique (odometry) and SLAM-ICP with the recursive method that is already implemented on the Robucar.

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