Abstract
For the issue of increased computational complexity to improve the positioning accuracy of robots leaving in the mobile robot localization method, this paper propose a new Monte Carlo localization algorithm. This method combinated the traditional particle filter algorithm with unscented Kalman filter, markovian Monte Carlo and reduced complexities level through dynamically updating the number of particles in particle collection and ensuring the accuracy of mobile robot localization. Simulation results show that the algorithm can not only inhibit the particle degradation and improve the positioning accuracy of the robot, but also in terms of computational complexity has increased significantly.
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© 2011 Springer-Verlag Berlin Heidelberg
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Chen, L., Sun, P., Zhang, G., Niu, J., Zhang, X. (2011). Fast Monte Carlo Localization for Mobile Robot. In: Shen, G., Huang, X. (eds) Advanced Research on Electronic Commerce, Web Application, and Communication. ECWAC 2011. Communications in Computer and Information Science, vol 144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20370-1_34
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DOI: https://doi.org/10.1007/978-3-642-20370-1_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20369-5
Online ISBN: 978-3-642-20370-1
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