多旋翼微型飞行器(MAVs)的生物启发分类和进化:全面回顾

IF 4.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Syed Waqar Hameed , Nursultan Imanberdiyev , Efe Camci , Wei-Yun Yau , Mir Feroskhan
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引用次数: 0

摘要

多旋翼微型飞行器(MAV)已成为监控、灾害管理和空中巡查等许多应用中必不可少的设备。这些应用的多样化需求催生了众多设计创新,使无人飞行器的发展突飞猛进。然而,这种增长使得了解基于功能和特征的无人飞行器设计的演变和分类变得非常具有挑战性。为了应对这一挑战,我们引入了一个新颖的、受生物启发的无人飞行器分类框架。我们的框架分为六个等级,每个等级包含一组不同的类别,从不同的设计角度对无人飞行器进行分类。它可以对文献中的无人飞行器设计进行适当比较,揭示它们的主要异同点。它还有助于追踪无人飞行器随时间推移的演变过程,确定研究趋势和潜在差距。最后,它还提供了对未来无人飞行器设计轨迹的见解,让人们对无人飞行器设计领域有一个完整而清晰的认识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bio-inspired classification and evolution of multirotor Micro Aerial Vehicles (MAVs): A comprehensive review
Multirotor Micro Aerial Vehicles (MAVs) have become essential in many applications like surveillance, disaster management, and aerial inspection. The diverse demands of these applications have led to numerous design innovations, growing the MAV landscape substantially. However, such growth has made it challenging to understand the evolution and classification of MAV designs based on their functions and features. We address this challenge by introducing a novel, bio-inspired taxonomic classification framework for MAVs. Our framework spans six hierarchical ranks, each containing a diverse set of categories that classify MAVs from distinct design perspectives. It enables a proper comparison of the MAV designs in the literature, revealing their key similarities and differences. It also helps to trace the evolution of MAVs over time, identifying research trends and potential gaps. Lastly, it offers insights into future MAV design trajectories, providing a complete and clear understanding of the MAV design landscape.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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