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An Improved UFastSLAM With Generalized Correntropy Loss and Adaptive Genetic Resampling

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  • Robot and Applications
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Abstract

The simultaneous localization and mapping (SLAM) is a research hotspot in robot navigation. In this paper, an improved UFastSLAM with generalized correntropy loss and adaptive genetic resampling is proposed. Specifically, the unscented Kalman filter algorithm with generalized correntropy loss is improved as the importance sampling in particle filter. Then, an adaptive genetic algorithm is employed to complete the resampling of particle filter. Finally, the improved UFastSLAM with generalized correntropy loss is presented to complete robot tracking. The proposed algorithm can complete robot tracking with high accuracy performance, and obtain reliable state estimation under the non-Gaussian measurement noise in SLAM. Simulation and experiment results exhibit the availability of the proposed SLAM algorithm.

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Authors and Affiliations

  1. School of Physics and Electronic Technology, Liaoning Normal University (LNNU), No. 850 Huanghe Road, Shahekou District, Dalian, 116029, China

    Ming Tang

  2. School of Information and Communication Engineering, Dalian University of Technology (DUT), No. 2 Linggong Road, Ganjingzi District, Dalian, 116024, China

    Ming Tang, Zhe Chen & Fuliang Yin

Authors
  1. Ming Tang
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  2. Zhe Chen
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  3. Fuliang Yin
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Correspondence to Fuliang Yin.

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This work was supported by National Natural Science Foundation of China (Nos.62271103,61871066), National High Technology Research and Development Program (863 Program) of China (No.2015AA016306), Natural Science Foundation of Liaoning Province of China (No.20170540159), Fundamental Research Funds for the Central Universities of China (No.DUT17LAB04), Basic Scientific Research Program for Educational Department of Liaoning Province of China (No. JYTQN2023264), Doctoral Initiation Scientific Research Program for Liaoning Normal University of China (No. 2023BSL013), and Provincial Innovation and Entrepreneurship Training Plan Program for Undergraduate of Liaoning Province of China (No. S202310165019).

Ming Tang received his B.S. degree in electronic information engineering, and an M.S. degree in optics from Liaoning Normal University (LNNU), Dalian, China, in 2012 and 2016, respectively, and a Ph.D. degree in signal and information processing from Dalian University of Technology (DUT), Dalian, China, in 2022. He joined the Department of Electronic Information Engineering, LNNU, as a Lecturer since 2022. His research interests include image processing, robot localization and tracking.

Zhe Chen received his B.S. degree in electronic engineering, M.S. and Ph.D. degrees in signal and information processing from Dalian University of Technology (DUT), Dalian, China, in 1996, 1999 and 2003, respectively. He joined the Department of Electronic Engineering, DUT, as a lecturer in 2002, became an associate professor in 2006, and has been a professor since 2017. His research interests include speech processing, image processing, and wideband wireless communication.

Fuliang Yin was born in Fushun city, Liaoning province, China, in 1962. He received his B.S. degree in electronic engineering and an M.S. degree in communications and electronic systems from Dalian University of Technology (DUT), Dalian, China, in 1984 and 1987, respectively. He joined the Department of Electronic Engineering, DUT, as a Lecturer in 1987 and became an Associate Professor in 1991. He has been a Professor at DUT since 1994, and the Dean of the School of Electronic and Information Engineering of DUT from 2000 to 2009. His research interests include speech processing, image processing, and broadband wireless communication.

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Tang, M., Chen, Z. & Yin, F. An Improved UFastSLAM With Generalized Correntropy Loss and Adaptive Genetic Resampling. Int. J. Control Autom. Syst. 22, 976–988 (2024). https://doi.org/10.1007/s12555-022-0535-4

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  • DOI: https://doi.org/10.1007/s12555-022-0535-4

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