مروری بر کاربرد الگوریتم‌های بهینه‌سازی الهام گرفته‌شده از طبیعت در طراحی مسیر وسایل پرنده

شفیعی نژاد, ایمان; بنی طالبی دهکردی, محمدرضا; نوریان پور, محمدامین

doi:10.22034/jtae.2024.8.3.6

مروری بر کاربرد الگوریتم‌های بهینه‌سازی الهام گرفته‌شده از طبیعت در طراحی مسیر وسایل پرنده

نوع مقاله : علمی- ترویجی

نویسندگان

ایمان شفیعی نژاد ¹

محمدرضا بنی طالبی دهکردی ²

محمدامین نوریان پور ²

¹ استادیار، پژوهشگاه هوافضا، وزارت علوم تحقیقات و فناوری، تهران، ایران

² کارشناسی، گروه مهندسی هوافضا، دانشگاه آزاد اسلامی واحد علوم تحقیقات، تهران، ایران

10.22034/jtae.2024.8.3.6

چکیده

در این مقاله به مروری بر کاربرد الگوریتم‌های ‌بهینه‌سازی الهام گرفته شده از طبیعت در طراحی مسیر وسایل پرنده پرداخته ‌شده‌است. افزایش چشمگیر قابلیت‌ها و در دسترس بودن ابزارهای زمینی و هوایی مستقل، چالش‌های ایمنی و امنیتی را به ویژه در حفاظت از زیرساخت‌های استراتژیک حائز اهمیت می‌کند. در این زمینه، رهگیری تهدیدات موبایلی متعدد با هدف تهاجم به فضاهای محدود این زیرساخت‌ها موضوع مهمی است. این مقاله بر روی مشکل برنامه ریزی مسیر برای رهگیری چندین هدف هوایی توسط گروهی از پهپادها تمرکز دارد. برنامه ریزی مسیر سه بعدی برای رهگیری اهداف متحرک یک کار چالش برانگیز است، به ویژه زمانی که رهگیری توسط انبوهی از پهپادها انجام می‌شود، زیرا محدودیت‌های حرکتی و دینامیکی متعددی وجود دارد. هدف ابتدا تخصیص اهداف به پهپادهای منفرد (تخصیص وظایف) و ایجاد یک مسیر سه بعدی برای هر یک است. بسیاری از الگوریتم‌ها به عنوان طرح‌های اصلی برای حل این نوع مسائل بر اساس هوش جمعی شناخته شده‌اند، بسیاری از آنها بر اساس سیستم‌های بیولوژیکی مانند بهینه‌سازی ازدحام ذرات، بهینه‌سازی کلونی مورچه‌ها، بهینه‌سازی کلونی زنبورهای مصنوعی، الگوریتم الهام گرفته از خفاش و غیره هستند. این مقاله مروری جامع از الگوریتم‌های هوش جمعی با محوریت مشکلات مربوط به برنامه‌ریزی مسیر سه بعدی برای رهگیری هدف توسط گروهی از پهپادها ارائه ‌شده‌است. همچنین بر بهبود الگوریتم‌های هوش جمعی موجود برای بهینه‌سازی مسیر بهینه تر و صحیح تر تمرکز می‌کند. یک بررسی جامع برای هر الگوریتم با تجزیه و تحلیل مزایا و معایب آن در زمینه رهگیری هدف نیز ارائه ‌شده‌است. این بررسی گسترده طرح کلی برای محققان و متخصصان در زمینه حرکت دسته جمعی پهپادها است.

کلیدواژه‌ها

بهینه‌سازی کلونی زنبور عسل

بهینه‌سازی ازدحام ذرات

بهینه‌سازی کلونی مورچه

کنترل گروهی وسایل پرنده

طراحی مسیر

موضوعات

مکانیک پرواز/ناوبری/کنترل/...

عنوان مقاله English

A Review of the Application of Optimization Algorithms Nature Inspired in the Design of Flight Paths

نویسندگان English

Iman Shafieenejad ¹

Mohammad Reza Banitalebi Dehkordi ²

Mohammad Amin Nourianpour ²

¹ Assistant Professor, Aerospace Research Institute, Ministry of Science Research and Technology. Tehran, Iran

² B. Sc. Department of Aerospace Engineering, Islamic Azad University Science and Research Branch.Tehran, Iran

چکیده English

In this article, an overview of the application of optimization algorithms inspired by nature in the design of the flight path has been discussed. The significant increase in the capabilities and availability of independent ground and air tools makes safety and security challenges especially important in the protection of strategic infrastructure. In this context, the detection of multiple mobile threats with the aim of invading the limited spaces of these infrastructures is an important issue. This paper focuses on the trajectory planning problem for the interception of multiple aerial targets by a group of UAVs. 3D trajectory planning for the tracking of moving targets is a challenging task, especially when the tracking is performed by a crowd of UAVs, because there are numerous motion and dynamic constraints. The goal is first to assign targets to individual drones (task assignment) and create a 3D path for each one. Many algorithms are known as the main schemes to solve this kind of problem based on collective intelligence; many of them are based on biological systems such as particle swarm optimization, ant colony optimization, artificial bee colony optimization, bat-inspired algorithm, etc. This article presents a comprehensive review of collective intelligence algorithms focusing on 3D path planning problems for target tracking by a group of UAVs. It also focuses on improving existing collective intelligence algorithms for more optimal and correct path optimization. A comprehensive review of each algorithm with an analysis of its advantages and disadvantages in the context of target tracking is also provided. This extensive review is the outline for researchers and practitioners in the field of mass UAVs.

کلیدواژه‌ها English

Bee Colony Optimization

Particle Swarm Optimization

Ant Colony Optimization

Group Control of Flying Devices

Route Design

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