Online path planning for unmanned aerial vehicles to maximize instantaneous information
In this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2021-05-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/17298814211010379 |
| _version_ | 1818600304625582080 |
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| author | Halit Ergezer Kemal Leblebicioğlu |
| author_facet | Halit Ergezer Kemal Leblebicioğlu |
| author_sort | Halit Ergezer |
| collection | DOAJ |
| description | In this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate forbidden zones during a mission. Additionally, the significance and reliability of the information collected about a target are assumed to decrease with time. The proposed solution finds each vehicle’s path by solving an optimization problem over a planning horizon while obeying specific rules. The basic structure in our solution is the centralized task assignment problem, and it produces near-optimal solutions. The solution can handle moving, pop-up targets, and UAV loss. It is a complicated optimization problem, and its solution is to be produced in a very short time. To simplify the optimization problem and obtain the solution in nearly real time, we have developed some rules. Among these rules, there is one that involves the kinematic constraints in the construction of paths. There is another which tackles the real-time decision-making problem using heuristics imitating human-like intelligence. Simulations are realized in MATLAB environment. The planning algorithm has been tested on various scenarios, and the results are presented. |
| first_indexed | 2024-12-16T12:33:22Z |
| format | Article |
| id | doaj.art-a5a0d9c6cfb845c397dd20347cba588c |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-16T12:33:22Z |
| publishDate | 2021-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-a5a0d9c6cfb845c397dd20347cba588c2022-12-21T22:31:39ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142021-05-011810.1177/17298814211010379Online path planning for unmanned aerial vehicles to maximize instantaneous informationHalit Ergezer0Kemal Leblebicioğlu1 Mechatronics Engineering Department, , Ankara, Turkey Department of Electrical and Electronics Engineering, , Ankara, TurkeyIn this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate forbidden zones during a mission. Additionally, the significance and reliability of the information collected about a target are assumed to decrease with time. The proposed solution finds each vehicle’s path by solving an optimization problem over a planning horizon while obeying specific rules. The basic structure in our solution is the centralized task assignment problem, and it produces near-optimal solutions. The solution can handle moving, pop-up targets, and UAV loss. It is a complicated optimization problem, and its solution is to be produced in a very short time. To simplify the optimization problem and obtain the solution in nearly real time, we have developed some rules. Among these rules, there is one that involves the kinematic constraints in the construction of paths. There is another which tackles the real-time decision-making problem using heuristics imitating human-like intelligence. Simulations are realized in MATLAB environment. The planning algorithm has been tested on various scenarios, and the results are presented.https://doi.org/10.1177/17298814211010379 |
| spellingShingle | Halit Ergezer Kemal Leblebicioğlu Online path planning for unmanned aerial vehicles to maximize instantaneous information International Journal of Advanced Robotic Systems |
| title | Online path planning for unmanned aerial vehicles to maximize instantaneous information |
| title_full | Online path planning for unmanned aerial vehicles to maximize instantaneous information |
| title_fullStr | Online path planning for unmanned aerial vehicles to maximize instantaneous information |
| title_full_unstemmed | Online path planning for unmanned aerial vehicles to maximize instantaneous information |
| title_short | Online path planning for unmanned aerial vehicles to maximize instantaneous information |
| title_sort | online path planning for unmanned aerial vehicles to maximize instantaneous information |
| url | https://doi.org/10.1177/17298814211010379 |
| work_keys_str_mv | AT halitergezer onlinepathplanningforunmannedaerialvehiclestomaximizeinstantaneousinformation AT kemalleblebicioglu onlinepathplanningforunmannedaerialvehiclestomaximizeinstantaneousinformation |