In this paper a novel solution to the Simultaneous Localization and Mapping (SLAM) problem for a team of mobile robots is proposed. The algorithm aims at approximating the robots surrounding environment by a set of polynomials, ensuring high mapping performance and low communication cost. To this sake, once two robots meet, only the acquired polynomials data are exchanged. Also, the algorithm has been developed trying to minimize each robot computational requirements so that it can be implemented in a decentralized way. Numerical simulations are reported to show the effectiveness of the proposed solution.
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