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A new fallback beetle antennae search algorithm for path planning of mobile robots with collision-free capability

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Abstract

With the development of technology, mobile robots are becoming more and more common in industrial production and daily life. Various rules are set to ensure that mobile robots can move without collision. This paper proposes a novel intelligent optimization algorithm, named fallback beetle antennae search algorithm. Based on the analysis of biological habits, when the creature enters blind alley during the foraging process, it will retreat a distance and then restart the search process. We introduce a fallback mechanism in the traditional beetle antenna search algorithm. In addition, the proposed algorithm possesses the characteristic of low time complexity. It can plan a collision-free path in a short period of time. Moreover, the effectiveness and superiority of the algorithm are verified by simulations in different types of environments and comparisons with existing path planning algorithms.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (with Nos. 61401385 and 61702146), by Hong Kong Research Grants Council Early Career Scheme (with No. 25214015), by Departmental General Research Fund of Hong Kong Polytechnic University (with No. G.61.37.UA7L) and also by PolyU Central Research Grant (with No. G-YBMU).

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Authors and Affiliations

  1. Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China

    Qing Wu, Hao Lin, Zeyu Chen & Dechao Chen

  2. Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

    Yuanzhe Jin

  3. Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

    Shuai Li

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  1. Qing Wu
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  2. Hao Lin
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  3. Yuanzhe Jin
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  4. Zeyu Chen
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  5. Shuai Li
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Correspondence to Dechao Chen.

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Wu, Q., Lin, H., Jin, Y. et al. A new fallback beetle antennae search algorithm for path planning of mobile robots with collision-free capability. Soft Comput 24, 2369–2380 (2020). https://doi.org/10.1007/s00500-019-04067-3

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