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For the mobile robot Simultaneous Localization and Mapping (SLAM),a new algorithm is proposed, and named Adaptive Iterated Square-Root Cubature Kalman Filter based SLAM algorithm (AISRCKF-SLAM). The main contribution of the algorithm is that the numerical integration method based on cubature rule is directly used to calculate the SLAM posterior probability(More)
When multiple mobile robots cooperatively explore an unknown environment, the advantages of robustness and redundancy are guaranteed. However, available traditional economy approaches for coordination of multi-robot systems (MRS) exploration lack efficient target selection strategy under a few of situations and rely on a perfect communication. In order to(More)
The lack of the latest measurement information and the Particle serious degradation cause low estimation precision in the tradition particle filter SLAM (simultaneous localization and mapping). For solve this problem, a SRCPF-SLAM (square cubature particle filter simultaneous localization and mapping) is proposed in this paper. The algorithm fuses the(More)
The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. In recent years, various methods for comparing the means of two independent log-normal distributions have been developed. In this paper a higher-order likelihood-based method is proposed. The method is applied to two real-life examples and(More)
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