Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning
The research of mobile robot path planning has shifted from the static environment to the dynamic environment, from the two-dimensional environment to the high-dimensional environment, and from the single-robot system to the multi-robot system. As the core technology for mobile robots to realize aut...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/15/3263 |
| _version_ | 1797586857413836800 |
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| author | Yiqi Xu Qiongqiong Li Xuan Xu Jiafu Yang Yong Chen |
| author_facet | Yiqi Xu Qiongqiong Li Xuan Xu Jiafu Yang Yong Chen |
| author_sort | Yiqi Xu |
| collection | DOAJ |
| description | The research of mobile robot path planning has shifted from the static environment to the dynamic environment, from the two-dimensional environment to the high-dimensional environment, and from the single-robot system to the multi-robot system. As the core technology for mobile robots to realize autonomous positioning and navigation, path-planning technology should plan collision-free and smooth paths for mobile robots in obstructed environments, which requires path-planning algorithms with a certain degree of intelligence. Metaheuristic algorithms are widely used in various optimization problems due to their algorithmic intelligence, and they have become the most effective algorithm to solve complex optimization problems in the field of mobile robot path planning. Based on a comprehensive analysis of existing path-planning algorithms, this paper proposes a new algorithm classification. Based on this classification, we focus on the firefly algorithm (FA) and the cuckoo search algorithm (CS), complemented by the dragonfly algorithm (DA), the whale optimization algorithm (WOA), and the sparrow search algorithm (SSA). During the analysis of the above algorithms, this paper summarizes the current research results of mobile robot path planning and proposes the future development trend of mobile robot path planning. |
| first_indexed | 2024-03-11T00:29:06Z |
| format | Article |
| id | doaj.art-2142c5b21b8b433daafb9760803d89c1 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T00:29:06Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-2142c5b21b8b433daafb9760803d89c12023-11-18T22:48:40ZengMDPI AGElectronics2079-92922023-07-011215326310.3390/electronics12153263Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path PlanningYiqi Xu0Qiongqiong Li1Xuan Xu2Jiafu Yang3Yong Chen4College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaThe research of mobile robot path planning has shifted from the static environment to the dynamic environment, from the two-dimensional environment to the high-dimensional environment, and from the single-robot system to the multi-robot system. As the core technology for mobile robots to realize autonomous positioning and navigation, path-planning technology should plan collision-free and smooth paths for mobile robots in obstructed environments, which requires path-planning algorithms with a certain degree of intelligence. Metaheuristic algorithms are widely used in various optimization problems due to their algorithmic intelligence, and they have become the most effective algorithm to solve complex optimization problems in the field of mobile robot path planning. Based on a comprehensive analysis of existing path-planning algorithms, this paper proposes a new algorithm classification. Based on this classification, we focus on the firefly algorithm (FA) and the cuckoo search algorithm (CS), complemented by the dragonfly algorithm (DA), the whale optimization algorithm (WOA), and the sparrow search algorithm (SSA). During the analysis of the above algorithms, this paper summarizes the current research results of mobile robot path planning and proposes the future development trend of mobile robot path planning.https://www.mdpi.com/2079-9292/12/15/3263mobile robotpath planningmetaheuristic algorithmfirefly algorithmcuckoo search algorithm |
| spellingShingle | Yiqi Xu Qiongqiong Li Xuan Xu Jiafu Yang Yong Chen Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning Electronics mobile robot path planning metaheuristic algorithm firefly algorithm cuckoo search algorithm |
| title | Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning |
| title_full | Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning |
| title_fullStr | Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning |
| title_full_unstemmed | Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning |
| title_short | Research Progress of Nature-Inspired Metaheuristic Algorithms in Mobile Robot Path Planning |
| title_sort | research progress of nature inspired metaheuristic algorithms in mobile robot path planning |
| topic | mobile robot path planning metaheuristic algorithm firefly algorithm cuckoo search algorithm |
| url | https://www.mdpi.com/2079-9292/12/15/3263 |
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