Autonomous mobile robot positioning using Unscented HybridSLAM

This paper addresses a novel approach to Simultaneous Localization and Mapping problem called Unscented HybridSLAM. Analyzing loop closing as one of the most important aspects of SLAM is the major interest of this study. Closing a loop by an autonomous mobile robot can be tricky even in the presence of a correct data association in the process, especially, when the loop is considerably large. The main challenge is to maintain a track of all correlations among landmarks and the mobile robot using Unscented HybridSLAM. The performance of proposed algorithm is evaluated with a loop closing scenario simulation, then, the results are discussed and compared with other algorithms.

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