Journal of System Simulation
Abstract
Abstract: Aiming at the problem of the accumulation of linearization error in the nonlinear system linearizing of Simultaneous Localization and Mapping (SLAM) in mobile robot, an algorithm named multi measurement update was put forward according to the analysis of Fisher information. In order to compute the state estimation after each measurement update, the Fisher information weight relationship between prediction variable and update variable was made use of Due to a number of data association with an estimation which was more close to the real data than the former, the algorithm could achieve a more accuracy posterior state. As a result, it could decrease the linearization error and improving the precision of localization and mapping. The experiments made a comparison between the multi measurement update and single measurement update. It shows that the proposed method can efficiently reduce the robot pose error and map information error.
Recommended Citation
Xu, Yafang; Sun, Zuoleit; Zeng, Liansun; and Bo, Zhang
(2021)
"Mobile Robot SLAM Simulation with Multi Measurement Update,"
Journal of System Simulation: Vol. 27:
Iss.
6, Article 20.
DOI: 10.16182/j.cnki.joss.2015.06.020
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol27/iss6/20
First Page
1288
Revised Date
2014-11-19
DOI Link
https://doi.org/10.16182/j.cnki.joss.2015.06.020
Last Page
1293
CLC
TP242
Recommended Citation
Xu Yafang, Sun Zuoleit, Zeng Liansun, Zhang Bo. Mobile Robot SLAM Simulation with Multi Measurement Update[J]. Journal of System Simulation, 2015, 27(6): 1288-1293.
DOI
10.16182/j.cnki.joss.2015.06.020
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Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons