A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

doi:10.1007/s40436-021-00366-x

Advances in Manufacturing ›› 2022, Vol. 10 ›› Issue (1): 114-130.doi: 10.1007/s40436-021-00366-x

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

Zhen Zhang, Rui He, Kuo Yang

School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, People's Republic of China

收稿日期:2021-03-05 修回日期:2021-05-28 出版日期:2022-03-25 发布日期:2022-02-23
通讯作者: Zhen Zhang E-mail:zhangzhen_ta@shu.edu.cn
基金资助:
This research was jointly supported by the National Key R&D Program of China (Grant No. 2018YFB1309200) and the Opening Project of Shanghai Robot Industry R&D and Transformation Functional Platform.

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

Zhen Zhang, Rui He, Kuo Yang

School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, People's Republic of China

Received:2021-03-05 Revised:2021-05-28 Online:2022-03-25 Published:2022-02-23
Contact: Zhen Zhang E-mail:zhangzhen_ta@shu.edu.cn
Supported by:
This research was jointly supported by the National Key R&D Program of China (Grant No. 2018YFB1309200) and the Opening Project of Shanghai Robot Industry R&D and Transformation Functional Platform.

摘要/Abstract

摘要： In this paper, a bioinspired path planning approach for mobile robots is proposed. The approach is based on the sparrow search algorithm, which is an intelligent optimization algorithm inspired by the group wisdom, foraging, and anti-predation behaviors of sparrows. To obtain high-quality paths and fast convergence, an improved sparrow search algorithm is proposed with three new strategies. First, a linear path strategy is proposed, which can transform the polyline in the corner of the path into a smooth line, to enable the robot to reach the goal faster. Then, a new neighborhood search strategy is used to improve the fitness value of the global optimal individual, and a new position update function is used to speed up the convergence. Finally, a new multi-index comprehensive evaluation method is designed to evaluate these algorithms. Experimental results show that the proposed algorithm has a shorter path and faster convergence than other state-of-the-art studies.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00366-x

关键词: Path planning, Linear path strategy, Sparrow search algorithm, Multi-index comprehensive evaluation algorithm

Abstract: In this paper, a bioinspired path planning approach for mobile robots is proposed. The approach is based on the sparrow search algorithm, which is an intelligent optimization algorithm inspired by the group wisdom, foraging, and anti-predation behaviors of sparrows. To obtain high-quality paths and fast convergence, an improved sparrow search algorithm is proposed with three new strategies. First, a linear path strategy is proposed, which can transform the polyline in the corner of the path into a smooth line, to enable the robot to reach the goal faster. Then, a new neighborhood search strategy is used to improve the fitness value of the global optimal individual, and a new position update function is used to speed up the convergence. Finally, a new multi-index comprehensive evaluation method is designed to evaluate these algorithms. Experimental results show that the proposed algorithm has a shorter path and faster convergence than other state-of-the-art studies.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00366-x

Key words: Path planning, Linear path strategy, Sparrow search algorithm, Multi-index comprehensive evaluation algorithm

Zhen Zhang, Rui He, Kuo Yang. A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm[J]. Advances in Manufacturing, 2022, 10(1): 114-130.

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A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

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