A path planning method using modified harris hawks optimization algorithm for mobile robots
Path planning is a critical technology that could help mobile robots accomplish their tasks quickly. However, some path planning algorithms tend to fall into local optimum in complex environments. A path planning method using a modified Harris hawks optimization (MHHO) algorithm is proposed to addre...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2023-07-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1473.pdf |
| _version_ | 1797776373608087552 |
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| author | Cuicui Cai Chaochuan Jia Yao Nie Jinhong Zhang Ling Li |
| author_facet | Cuicui Cai Chaochuan Jia Yao Nie Jinhong Zhang Ling Li |
| author_sort | Cuicui Cai |
| collection | DOAJ |
| description | Path planning is a critical technology that could help mobile robots accomplish their tasks quickly. However, some path planning algorithms tend to fall into local optimum in complex environments. A path planning method using a modified Harris hawks optimization (MHHO) algorithm is proposed to address the problem and improve the path quality. The proposed method improves the performance of the algorithm through multiple strategies. A linear path strategy is employed in path planning, which could straighten the corner segments of the path, making the obtained path smooth and the path distance short. Then, to avoid getting into the local optimum, a local search update strategy is applied to the HHO algorithm. In addition, a nonlinear control strategy is also used to improve the convergence accuracy and convergence speed. The performance of the MHHO method was evaluated through multiple experiments in different environments. Experimental results show that the proposed algorithm is more efficient in path length and speed of convergence than the ant colony optimization (ACO) algorithm, improved sparrow search algorithm (ISSA), and HHO algorithms. |
| first_indexed | 2024-03-12T22:48:59Z |
| format | Article |
| id | doaj.art-548bbbb26e4342a78bdfdc12c2af5ae0 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-12T22:48:59Z |
| publishDate | 2023-07-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-548bbbb26e4342a78bdfdc12c2af5ae02023-07-20T15:05:13ZengPeerJ Inc.PeerJ Computer Science2376-59922023-07-019e147310.7717/peerj-cs.1473A path planning method using modified harris hawks optimization algorithm for mobile robotsCuicui Cai0Chaochuan Jia1Yao Nie2Jinhong Zhang3Ling Li4College of Electronics and Information Engineering, West Anhui University, Lu’an, ChinaCollege of Electronics and Information Engineering, West Anhui University, Lu’an, ChinaCollege of Electronics and Information Engineering, West Anhui University, Lu’an, ChinaCollege of Electronics and Information Engineering, West Anhui University, Lu’an, ChinaCollege of Electronics and Information Engineering, West Anhui University, Lu’an, ChinaPath planning is a critical technology that could help mobile robots accomplish their tasks quickly. However, some path planning algorithms tend to fall into local optimum in complex environments. A path planning method using a modified Harris hawks optimization (MHHO) algorithm is proposed to address the problem and improve the path quality. The proposed method improves the performance of the algorithm through multiple strategies. A linear path strategy is employed in path planning, which could straighten the corner segments of the path, making the obtained path smooth and the path distance short. Then, to avoid getting into the local optimum, a local search update strategy is applied to the HHO algorithm. In addition, a nonlinear control strategy is also used to improve the convergence accuracy and convergence speed. The performance of the MHHO method was evaluated through multiple experiments in different environments. Experimental results show that the proposed algorithm is more efficient in path length and speed of convergence than the ant colony optimization (ACO) algorithm, improved sparrow search algorithm (ISSA), and HHO algorithms.https://peerj.com/articles/cs-1473.pdfPath planningHarris hawks optimization algorithmMobile robotObstacle avoidanceOptimal path |
| spellingShingle | Cuicui Cai Chaochuan Jia Yao Nie Jinhong Zhang Ling Li A path planning method using modified harris hawks optimization algorithm for mobile robots PeerJ Computer Science Path planning Harris hawks optimization algorithm Mobile robot Obstacle avoidance Optimal path |
| title | A path planning method using modified harris hawks optimization algorithm for mobile robots |
| title_full | A path planning method using modified harris hawks optimization algorithm for mobile robots |
| title_fullStr | A path planning method using modified harris hawks optimization algorithm for mobile robots |
| title_full_unstemmed | A path planning method using modified harris hawks optimization algorithm for mobile robots |
| title_short | A path planning method using modified harris hawks optimization algorithm for mobile robots |
| title_sort | path planning method using modified harris hawks optimization algorithm for mobile robots |
| topic | Path planning Harris hawks optimization algorithm Mobile robot Obstacle avoidance Optimal path |
| url | https://peerj.com/articles/cs-1473.pdf |
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