Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios
Many sectors in aerial transportation use unmanned aircraft vehicles (UAVs) extensively. This becomes even more challenging in complex environments where not only it is required to avoid obstacles, but it also must be maintained for a prolonged period of time. This paper presents a novel approach to...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Ain Shams Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447925000425 |
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| author | Mushtaq Muhammad Umer Hein Venter Owais Muhammad Tamoor Shafique Fuad A. Awwad Emad A.A. Ismail |
| author_facet | Mushtaq Muhammad Umer Hein Venter Owais Muhammad Tamoor Shafique Fuad A. Awwad Emad A.A. Ismail |
| author_sort | Mushtaq Muhammad Umer |
| collection | DOAJ |
| description | Many sectors in aerial transportation use unmanned aircraft vehicles (UAVs) extensively. This becomes even more challenging in complex environments where not only it is required to avoid obstacles, but it also must be maintained for a prolonged period of time. This paper presents a novel approach to increase UAV autonomy through safe and efficient flight trajectory design. An optimization problem is formulated with external and internal safety constraints, and traversing collision free paths. The proposed work offers an energy efficient RRT algorithm, which is used to assess multiple trajectory alternatives. The simulation results confirm the achieved performance in finding the optimal energy path while obeying to the safety constraint. The data and performance metrics, show the system operated in a safe and energy efficient manner. This work provides a unified framework for UAV trajectory planning that guarantees a trade-off between safety and energy efficiency. |
| format | Article |
| id | doaj-art-5d5cd8cc7ee145a0a365b1f8ece25cc6 |
| institution | Kabale University |
| issn | 2090-4479 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj-art-5d5cd8cc7ee145a0a365b1f8ece25cc62025-02-08T05:00:09ZengElsevierAin Shams Engineering Journal2090-44792025-03-01163103301Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenariosMushtaq Muhammad Umer0Hein Venter1Owais Muhammad2Tamoor Shafique3Fuad A. Awwad4Emad A.A. Ismail5Department of Computer Science, University of Pretoria, Pretoria, South Africa; Corresponding authors.Department of Computer Science, University of Pretoria, Pretoria, South Africa; Corresponding authors.School of Information Engineering, SWUST, Mianyang, ChinaSchool of Digital Technology, Innovation and Business, University of Staffordshire, United KingdomDepartment of Quantitative Analysis, College of Business Administration, King Saud University, P.O.Box 71115, Riyadh 11587, Saudi ArabiaDepartment of Quantitative Analysis, College of Business Administration, King Saud University, P.O.Box 71115, Riyadh 11587, Saudi ArabiaMany sectors in aerial transportation use unmanned aircraft vehicles (UAVs) extensively. This becomes even more challenging in complex environments where not only it is required to avoid obstacles, but it also must be maintained for a prolonged period of time. This paper presents a novel approach to increase UAV autonomy through safe and efficient flight trajectory design. An optimization problem is formulated with external and internal safety constraints, and traversing collision free paths. The proposed work offers an energy efficient RRT algorithm, which is used to assess multiple trajectory alternatives. The simulation results confirm the achieved performance in finding the optimal energy path while obeying to the safety constraint. The data and performance metrics, show the system operated in a safe and energy efficient manner. This work provides a unified framework for UAV trajectory planning that guarantees a trade-off between safety and energy efficiency.http://www.sciencedirect.com/science/article/pii/S2090447925000425Energy-efficient trajectory planningUnmanned aircraft vehicles (UAVs)Obstacle avoidanceOptimizationReal-time applications |
| spellingShingle | Mushtaq Muhammad Umer Hein Venter Owais Muhammad Tamoor Shafique Fuad A. Awwad Emad A.A. Ismail Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios Ain Shams Engineering Journal Energy-efficient trajectory planning Unmanned aircraft vehicles (UAVs) Obstacle avoidance Optimization Real-time applications |
| title | Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios |
| title_full | Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios |
| title_fullStr | Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios |
| title_full_unstemmed | Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios |
| title_short | Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios |
| title_sort | cognitive strategies for uav trajectory optimization ensuring safety and energy efficiency in real world scenarios |
| topic | Energy-efficient trajectory planning Unmanned aircraft vehicles (UAVs) Obstacle avoidance Optimization Real-time applications |
| url | http://www.sciencedirect.com/science/article/pii/S2090447925000425 |
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