فصلنامه علمی کارافن

فصلنامه علمی کارافن

برنامه‌ریزی مسیر سه‌بعدی پهپادها در شبکه‌های حسگر بیسیم مبتنی بر بهینه‌سازی گرگ خاکستری

نوع مقاله : مقاله پژوهشی (کاربردی)

نویسندگان
1 دکتری مهندسی کامپیوتر، دانشکده برق و کامپیوتر دانشگاه کاشان.
2 استادیار گروه مهندسی کامپیوتر- نرم‌افزار ، دانشکده برق و کامپیوتر دانشگاه کاشان.
3 استادیار گروه مهندسی کامپیوتر- نرم‌افزار، دانشکده کامپیوتر دانشگاه تربیت دبیر شهید رجایی تهران.
چکیده
در این پژوهش، یک چارچوب ترکیبی برای استقرار و برنامه‌ریزی مسیر پهپادها در شبکه‌های حسگر بی‌سیم ارائه می‌شود. در گام نخست، الگوریتم میدان پتانسیل مصنوعی به منظور ارزش‌گذاری محیط و اجتناب از موانع به‌کار گرفته شده است. سپس نسخه توسعه‌یافته الگوریتم NSGA-II برای توزیع بهینه پهپادها در محیط مورد استفاده قرار گرفته تا پوشش مناطق با ارزش اطلاعاتی بیشینه و همپوشانی میدان دید کاهش یابد. در ادامه، الگوریتم گرگ خاکستری چندهدفه برای طراحی مسیرهای پروازی ایمن و کارآمد به کار گرفته شده است. شبیه‌سازی‌ها بر اساس مدل ارتفاع رقومی سه‌بعدی واقعی و در دو سناریوی متفاوت، شامل شرایط با الزام ارتباطی و بدون الزام ارتباطی، انجام شده است. نتایج نشان می‌دهد که چارچوب پیشنهادی به طور میانگین بیش از ۸۵ درصد پوشش اطلاعاتی و بیش از ۹۰ درصد موفقیت در همگرایی به دست می‌آورد و در مقایسه با الگوریتم‌های مرجع نظیر PSO و GA عملکرد بهتری ارائه می‌دهد. تحلیل‌های آماری شامل میانگین، انحراف معیار و آزمون t نیز اعتبار نتایج را تأیید می‌کند. این چارچوب می‌تواند به عنوان رویکردی کارآمد و مقیاس‌پذیر برای پایش هوشمند محیط‌های پیچیده مورد استفاده قرار گیرد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

UAV 3D path planning in wireless sensor networks based on gray wolf optimization

نویسندگان English

hakimeh mazaheri 1
salman goli 2
ali nourollah 3
1 PhD in Computer Engineering, Faculty of Electrical and Computer Science, Kashan University.
2 Assistant Professor, Department of Computer Engineering – Software, Electrical and Computer Faculty of Kashan University.
3 Assistant Professor, Department of Computer Engineering – Software, Computer Faculty of Tarbiat University, Shahid Rajaee, Tehran.
چکیده English

This study introduces a hybrid framework for unmanned aerial vehicle (UAV) deployment and path planning in wireless sensor networks. The proposed approach integrates three complementary components: an artificial potential field (APF) method to evaluate the informational value of environmental regions and ensure obstacle avoidance, an enhanced NSGA-II algorithm to achieve an efficient spatial distribution of UAVs with minimal overlap, and a multi-objective grey wolf optimizer (GWO) to generate collision-free and energy-aware flight trajectories within a hierarchical UAV structure. Simulations are conducted on a realistic three-dimensional digital elevation model (DEM) under two scenarios, with and without communication constraints. The results demonstrate that the proposed framework consistently achieves more than 85% information coverage and over 90% convergence success, outperforming benchmark algorithms such as PSO and GA. Statistical analyses, including mean, standard deviation, and t-tests, further confirm the robustness and significance of the findings. Overall, the framework provides a scalable and effective solution for intelligent monitoring of complex environments.

کلیدواژه‌ها English

UAV 3D Path Planning
Wireless Sensor Networks
Gray Wolf Optimization
Artificial Potential Field
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دوره 23، شماره 1
فنی و مهندسی
بهار 1405
صفحه 428-458

  • تاریخ دریافت 16 تیر 1404
  • تاریخ بازنگری 11 مهر 1404
  • تاریخ پذیرش 12 آذر 1404