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A novel robust approach for SLAM of mobile robot

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Abstract

The task of simultaneous localization and mapping (SLAM) is to build environmental map and locate the position of mobile robot at the same time. FastSLAM 2.0 is one of powerful techniques to solve the SLAM problem. However, there are two obvious limitations in FastSLAM 2.0, one is the linear approximations of nonlinear functions which would cause the filter inconsistent and the other is the “particle depletion” phenomenon. A kind of PSO & H ∞-based FastSLAM 2.0 algorithm is proposed. For maintaining the estimation accuracy, H ∞ filter is used instead of EKF for overcoming the inaccuracy caused by the linear approximations of nonlinear functions. The unreasonable proposal distribution of particle greatly influences the pose state estimation of robot. A new sampling strategy based on PSO (particle swarm optimization) is presented to solve the “particle depletion” phenomenon and improve the accuracy of pose state estimation. The proposed approach overcomes the obvious drawbacks of standard FastSLAM 2.0 algorithm and enhances the robustness and efficiency in the parts of consistency of filter and accuracy of state estimation in SLAM. Simulation results demonstrate the superiority of the proposed approach.

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Authors and Affiliations

  1. School of Astronautics, Harbin Institute of Technology, Harbin, 150001, China

    Jia-chen Ma  (马家辰), Qi Zhang  (张琦) & Li-yong Ma  (马立勇)

  2. School of Informations and Electrical Engineering, Harbin Institute of Technology at Weihai, Weihai, 264209, China

    Jia-chen Ma  (马家辰)

Authors
  1. Jia-chen Ma  (马家辰)
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  2. Qi Zhang  (张琦)
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  3. Li-yong Ma  (马立勇)
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Corresponding author

Correspondence to Qi Zhang  (张琦).

Additional information

Foundation item: Project(ZR2011FM005) supported by the Natural Science Foundation of Shandong Province, China

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Ma, Jc., Zhang, Q. & Ma, Ly. A novel robust approach for SLAM of mobile robot. J. Cent. South Univ. 21, 2208–2215 (2014). https://doi.org/10.1007/s11771-014-2172-4

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  • DOI: https://doi.org/10.1007/s11771-014-2172-4

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