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Design and implementation of intelligent LiDAR SLAM for autonomous mobile robots using evolutionary normal distributions transform

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Abstract

This paper presents a method that employs an evolutionary normal distributions transform (NDT) for simultaneous localization and mapping (SLAM) using light detection and ranging (LiDAR) for autonomous mobile robots. An adaptive inertia weight and two genetic operators were employed in the Taguchi-based whale optimization algorithm (WOA) to improve the search diversity and avoid local optima. NDT was used to model the environment of differential-drive mobile robots and WOA was applied to optimize the scan matching for the robotic SLAM problem. The NDT-WOA determines the SLAM pose estimation using sensed data from the physical world. A nonholonomic mobile robot was steered to achieve the NDT-WOA SLAM task with the derived robot kinematics and actuator dynamics. The proposed method was implemented in a TurtleBot3 Burger robotic development kit, which includes a single-board computer and an OpenCR control board. The Robot Operating System (ROS) was utilized to implement the evolutionary NDT-WOA SLAM system due to its flexibility, open source, and client library. Simulation and comparisons were conducted to illustrate the efficiency of the proposed NDT-WOA SLAM method compared to other SLAM paradigms. The experimental results show the effectiveness of the proposed evolutionary NDT-WOA SLAM for autonomous mobile robots. The results could have theoretical and practical significance for robotics research.

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Acknowledgements

The authors are grateful to the anonymous reviewers for their constructive comments to improve the quality of this paper.

Funding

This work was supported in part by the Ministry of Science and Technology (MOST), Taiwan, under Grants MOST 110-2221-E-011-121, MOST 110-2221-E-197-031, and MOST 111-2221-E-011-146-MY2.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Ilan University, Yilan, 260007, Taiwan

    Hsu-Chih Huang & Yu-Xiang Chen

  2. Graduate Institute of Automation and Control, National Taiwan University of Science and Technology, Taipei, 106335, Taiwan

    Sendren Sheng-Dong Xu, Hsien-Chan Lin & Yuan-Sheng Xiao

  3. Advanced Manufacturing Research Center, National Taiwan University of Science and Technology, Taipei, 106335, Taiwan

    Sendren Sheng-Dong Xu

Authors
  1. Hsu-Chih Huang
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  2. Sendren Sheng-Dong Xu
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  3. Hsien-Chan Lin
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  4. Yuan-Sheng Xiao
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  5. Yu-Xiang Chen
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Contributions

All authors contributed to the study’s conception, and participated in the literature survey, experimental design, and simulation analysis. H.-C. Lin and Y.-S. Xiao contributed software coding and physical experiments. H.-C. Huang contributed to the writing of the first draft of the manuscript. H.-C. Huang and S. S.-D. Xu contributed to the revision of this paper. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Sendren Sheng-Dong Xu.

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Huang, HC., Xu, S.SD., Lin, HC. et al. Design and implementation of intelligent LiDAR SLAM for autonomous mobile robots using evolutionary normal distributions transform. Soft Comput 28, 5321–5337 (2024). https://doi.org/10.1007/s00500-023-09219-0

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