Nature-Inspired Algorithm Based Trajectory Planning for Inspection Flying Robot in Smart Grids

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dc.authorscopusidİlhami Çolak / 6602990030
dc.authorwosidİlhami Çolak / ABI-4240-2020
dc.contributor.authorTenniche, Nesrine
dc.contributor.authorBoubekeur, Mendil
dc.contributor.authorHocine, Lehouche
dc.contributor.authorBelkaid, Abdelhakim
dc.contributor.authorÇolak, İlhami
dc.contributor.authorTighzert, Lyes
dc.date.accessioned2025-04-18T10:02:22Z
dc.date.available2025-04-18T10:02:22Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description.abstractDeveloping new trends and technologies for power line inspection is critical for smart grid reliability. Due to the drawbacks of traditional power line methods, such as time consumption, high costs, and risks to worker's safety, innovative technologies like flying robots need to be incorporated. Trajectory planning is crucial for optimizing path and conserving energy during flight, addressing challenges like collision avoidance, real-time planning, dynamic environments, and high-dimensional state spaces, for reliable motion of flying robots in inspection tasks. This study introduces a new trajectory planner for a flying robot, called quadrotor, designed for inspecting power lines within a smart grid infrastructure. The proposed approach utilizes the Water Cycle Algorithm (WCA) to find the most efficient trajectory within the 3D environment surrounding the power lines. The WCA algorithm emulates the water cycle's dynamic processes, considering path length as an objective function while incorporating constraints such as collision avoidance, velocity limits, non-holonomic constraints, and execution time. The WCA's performance was evaluated against the Firefly Algorithm (FA) and the Particle Swarm Optimization (PSO), demonstrating superior path length minimization and enhancing efficiency for power line inspection in smart grids. © 2024 IEEE.
dc.description.sponsorshipThis study, conducted at the Department of Automatic, Telecommunications and Electronics, Faculty of Technology, Bejaia University, Algeria, received support from the PRFU research project No. A01L08UN060120220001; and by the Faculty of Engineering and Natural Science of Istinye University, Istanbul, Turkey. We greatly appreciate this support.
dc.identifier.citationTenniche, N., Boubekeur, M., Hocine, L., Belkaid, A., Colak, I., & Tighzert, L. (2024, May). Nature-Inspired Algorithm Based Trajectory Planning for Inspection Flying Robot in Smart Grids. In 2024 12th International Conference on Smart Grid (icSmartGrid) (pp. 270-276). IEEE.
dc.identifier.doi10.1109/icSmartGrid61824.2024.10578104
dc.identifier.endpage276
dc.identifier.isbn979-835036161-2
dc.identifier.scopus2-s2.0-85199442515
dc.identifier.startpage270
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6928
dc.identifier.wosWOS:001266130300040
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorÇolak, İlhami
dc.institutionauthoridİlhami Çolak / 0000-0002-6405-5938
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof12th International Conference on Smart Grid, icSmartGrid 2024
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFlying Robots
dc.subjectOptimization
dc.subjectPower Line İnspection
dc.subjectSmart Grid
dc.subjectWater Cycle Algorithm
dc.titleNature-Inspired Algorithm Based Trajectory Planning for Inspection Flying Robot in Smart Grids
dc.typeOther

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