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When solving the problem of simultaneous localization and mapping (SLAM), a standard extended Kalman filter (EKF) is subject
to linearization errors and causes optimistic estimation. This paper proposes a submap algorithm, which builds a weighted
least squares (WLS) constraint between two adjacent submaps according to the different estimations of the common features
and the relationship between the vehicle poses in the corresponding submaps. By establishing the constraint equation after
loop closing, re-linearization is implemented and each submap’s reference frame tends to its equilibrium position quickly.
Experimental results demonstrate that the algorithm could get a globally consistent map and linearization errors are limited
in local regions. 相似文献
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钱钧 《郑州铁路职业技术学院学报》2008,20(2):50-51
通过体检B超及生化检查探寻脂肪肝的发病原因,可看出151例脂肪肝生化异常与病因密切相关。脂肪肝只要治疗及时是可以治愈的。 相似文献
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