Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things
It is a research topic of practical significance to study the path planning technology of mobile robot navigation technology. Aiming at the problems of slow convergence speed, redundant planning path, and easy to fall into local optimal value of ant colony algorithm in a complex environment, a robot...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/1739884 |
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| author | Hongliu Huang Guo Tan Linli Jiang |
| author_facet | Hongliu Huang Guo Tan Linli Jiang |
| author_sort | Hongliu Huang |
| collection | DOAJ |
| description | It is a research topic of practical significance to study the path planning technology of mobile robot navigation technology. Aiming at the problems of slow convergence speed, redundant planning path, and easy to fall into local optimal value of ant colony algorithm in a complex environment, a robot path planning based on improved ant colony algorithm is proposed. First, the grid method is used to model the path environment, which marks each grid to make the ant colony move from the initial grid to the target grid for path search. Second, the ant colony is divided according to different planning tasks. Let some ants explore the way first, and carry out basic optimization planning for the map environment. The antecedent ants mark the basic advantage on a target value of the path with pheromone concentration so as to guide the subsequent route-finding operation of the main ant colony. Finally, in order to avoid the individual ants falling into a deadlock state in the early search, the obstacle avoidance factor is increased, the transition probability is improved, and the amount of information on each path is dynamically adjusted according to the local path information, so as to avoid the excessive concentration of pheromones. Experimental results show that the algorithm has high global search ability, significantly speeds up the convergence speed, and can effectively improve the efficiency of mobile robot in path planning. |
| format | Article |
| id | doaj-art-833cfb66f9104a70986b8c5e10473f8f |
| institution | Kabale University |
| issn | 1687-9619 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-833cfb66f9104a70986b8c5e10473f8f2025-02-03T07:24:17ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/1739884Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of ThingsHongliu Huang0Guo Tan1Linli Jiang2School of Mathematics and Computer ScienceExperimental Training CentreSchool of Mathematics and Computer ScienceIt is a research topic of practical significance to study the path planning technology of mobile robot navigation technology. Aiming at the problems of slow convergence speed, redundant planning path, and easy to fall into local optimal value of ant colony algorithm in a complex environment, a robot path planning based on improved ant colony algorithm is proposed. First, the grid method is used to model the path environment, which marks each grid to make the ant colony move from the initial grid to the target grid for path search. Second, the ant colony is divided according to different planning tasks. Let some ants explore the way first, and carry out basic optimization planning for the map environment. The antecedent ants mark the basic advantage on a target value of the path with pheromone concentration so as to guide the subsequent route-finding operation of the main ant colony. Finally, in order to avoid the individual ants falling into a deadlock state in the early search, the obstacle avoidance factor is increased, the transition probability is improved, and the amount of information on each path is dynamically adjusted according to the local path information, so as to avoid the excessive concentration of pheromones. Experimental results show that the algorithm has high global search ability, significantly speeds up the convergence speed, and can effectively improve the efficiency of mobile robot in path planning.http://dx.doi.org/10.1155/2022/1739884 |
| spellingShingle | Hongliu Huang Guo Tan Linli Jiang Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things Journal of Robotics |
| title | Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things |
| title_full | Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things |
| title_fullStr | Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things |
| title_full_unstemmed | Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things |
| title_short | Robot Path Planning Using Improved Ant Colony Algorithm in the Environment of Internet of Things |
| title_sort | robot path planning using improved ant colony algorithm in the environment of internet of things |
| url | http://dx.doi.org/10.1155/2022/1739884 |
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