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HG-SMA: hierarchical guided slime mould algorithm for smooth path planning

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Abstract

The smooth path planning for mobile robots is attracted particular research attention. In this paper, an enhanced slime mould algorithm called HG-SMA is proposed to solve a new smooth path planning model based on the Said-Ball curve. Firstly, the enhanced algorithm is constructed by adding a hierarchical guided strategy. This strategy considers the characteristics of individuals with different fitness values, and divides the slime mould population into two hierarchies. And corresponding strategies are applied to different hierarchies to improve the quality of solutions. To validate the performance of the proposed HG-SMA algorithm, it is compared with other improved slime mould algorithms and classical meta-heuristic algorithms on test functions of CEC2017 and CEC2019 suites. Results show HG-SMA performs best on 74.36 and 79.49% of all 39 functions when compared with other improved SMA algorithms and classical optimization algorithms, respectively, which illustrates it is superior to others in solution accuracy, stability and convergence speed. Secondly, by regarding the control points as variables, a novel smooth path planning model based on Said-Ball curve is established to generate the feasible path for mobile robots. Compared with other traditional path planning approaches (A*, RRT and Informed RRT*), the Said-Ball curve-based approach can construct paths with higher smoothness, and has advantages in calculation speed compared with Bézier curve-based approach. Finally, the proposed HG-SMA is employed to solve the established optimization model based on Said-Ball curve, named the Said-Ball + HG-SMA approach. In three designed workplaces, HG-SMA also has advantages in generating feasible paths with shorter lengths and higher smoothness when compared with the original SMA and other classical algorithms.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grants No. 51875454 and 61772416).

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Authors and Affiliations

  1. Department of Applied Mathematics, Xi’an University of Technology, Xi’an, 710054, People’s Republic of China

    Gang Hu & Bo Du

  2. School of Computer Science and Engineering, Xi’an University of Technology, No. 5 South Jinhua Road, Xi’an, 710048, People’s Republic of China

    Gang Hu

  3. Department of Mathematics & Computer Science, University of North Carolina at Pembroke, Pembroke, NC, 28372, USA

    Guo Wei

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  1. Gang Hu
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  2. Bo Du
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GH, BD and GW wrote the main manuscript text and BD prepared all figures. All authors reviewed the manuscript.

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Correspondence to Gang Hu.

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Hu, G., Du, B. & Wei, G. HG-SMA: hierarchical guided slime mould algorithm for smooth path planning. Artif Intell Rev 56, 9267–9327 (2023). https://doi.org/10.1007/s10462-023-10398-3

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