Path planning in three-dimensional space based on butterfly optimization algorithm
Abstract Path planning is one of the most critical issues in many related fields including UAVs. Many researchers have addressed this problem according to different conditions and limitations, but modelling the 3-D space and routing with an evolutional algorithm in such spaces is an open issue. So,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-52750-9 |
| _version_ | 1797274913997848576 |
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| author | Hakimeh Mazaheri Salman Goli Ali Nourollah |
| author_facet | Hakimeh Mazaheri Salman Goli Ali Nourollah |
| author_sort | Hakimeh Mazaheri |
| collection | DOAJ |
| description | Abstract Path planning is one of the most critical issues in many related fields including UAVs. Many researchers have addressed this problem according to different conditions and limitations, but modelling the 3-D space and routing with an evolutional algorithm in such spaces is an open issue. So, in this paper, we first, introduce a method to grids the environment using geometrical shapes. This can reduce the random states of cell decomposition and increases the computational speed. We then propose an effective routing algorithm based on the butterfly optimization algorithm (BOA). It can simultaneously optimize multiple path planning objectives. It uses an objective function to compute the shortest path, based on obstacle avoidance and the UAV’s operational power minimization. A novel concept, the intelligent throwing agent, used in this algorithm prevents getting stuck in local optima and increases the network coverage in path planning. The throwing agent prevents the collision of the UAV with the obstacles using geometrical techniques and contour lines. The simulation results show that BOA has the least and second-least cost in best-case and worst-case scenarios in comparison with ant colony and particle swarm. Its run time and the optimal value of the fitting function are also better than the two other algorithms. |
| first_indexed | 2024-03-07T15:04:59Z |
| format | Article |
| id | doaj.art-1859ceb9f2554440baab55f1704f693c |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-07T15:04:59Z |
| publishDate | 2024-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-1859ceb9f2554440baab55f1704f693c2024-03-05T18:54:41ZengNature PortfolioScientific Reports2045-23222024-01-0114112110.1038/s41598-024-52750-9Path planning in three-dimensional space based on butterfly optimization algorithmHakimeh Mazaheri0Salman Goli1Ali Nourollah2Computer Department, Faculty of Electrical and Computer Engineering, University of KashanComputer Department, Faculty of Electrical and Computer Engineering, University of KashanComputer Department, Faculty of Computer Engineering, Shahid Rajaee Teacher Training UniversityAbstract Path planning is one of the most critical issues in many related fields including UAVs. Many researchers have addressed this problem according to different conditions and limitations, but modelling the 3-D space and routing with an evolutional algorithm in such spaces is an open issue. So, in this paper, we first, introduce a method to grids the environment using geometrical shapes. This can reduce the random states of cell decomposition and increases the computational speed. We then propose an effective routing algorithm based on the butterfly optimization algorithm (BOA). It can simultaneously optimize multiple path planning objectives. It uses an objective function to compute the shortest path, based on obstacle avoidance and the UAV’s operational power minimization. A novel concept, the intelligent throwing agent, used in this algorithm prevents getting stuck in local optima and increases the network coverage in path planning. The throwing agent prevents the collision of the UAV with the obstacles using geometrical techniques and contour lines. The simulation results show that BOA has the least and second-least cost in best-case and worst-case scenarios in comparison with ant colony and particle swarm. Its run time and the optimal value of the fitting function are also better than the two other algorithms.https://doi.org/10.1038/s41598-024-52750-9 |
| spellingShingle | Hakimeh Mazaheri Salman Goli Ali Nourollah Path planning in three-dimensional space based on butterfly optimization algorithm Scientific Reports |
| title | Path planning in three-dimensional space based on butterfly optimization algorithm |
| title_full | Path planning in three-dimensional space based on butterfly optimization algorithm |
| title_fullStr | Path planning in three-dimensional space based on butterfly optimization algorithm |
| title_full_unstemmed | Path planning in three-dimensional space based on butterfly optimization algorithm |
| title_short | Path planning in three-dimensional space based on butterfly optimization algorithm |
| title_sort | path planning in three dimensional space based on butterfly optimization algorithm |
| url | https://doi.org/10.1038/s41598-024-52750-9 |
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