MOMAV:一种高度对称的全驱动多旋翼无人机,采用优化控制分配

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Marco Ruggia
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引用次数: 0

摘要

MOMAV(马可的全方位微型飞行器)是一种完全驱动的多旋翼无人机,这意味着它可以独立于位置控制自己的方向。MOMAV也是高度对称的,使其飞行效率在很大程度上不受当前方向的影响。这些特点是通过一种新颖的无人机设计实现的,其中六个旋翼臂与八面体的顶点对齐,并且每个手臂可以沿着其长轴主动旋转。介绍了MOMAV的各种突出特点:与其他全驱动无人机的手臂配置相比,其飞行效率高,设计了具有滑环的原始旋转手臂组件,用于实现手臂的连续旋转,以及基于顺序二次规划(SQP)的新型控制分配算法,用于计算飞行中的油门和手臂角度设定点。飞行试验表明,MOMAV能够实现非常低的平均位置/方向误差,当扫描位置设定值为6.6 mm, 2.1°(σ: 3.0 mm, 1.0°),当扫描方向设定值为11.8 mm, 3.3°(σ: 8.6 mm, 2.0°)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MOMAV: A highly symmetrical fully-actuated multirotor drone using optimizing control allocation

MOMAV: A highly symmetrical fully-actuated multirotor drone using optimizing control allocation
MOMAV (Marco’s Omnidirectional Micro Aerial Vehicle) is a multirotor drone that is fully actuated, meaning it can control its orientation independently of its position. MOMAV is also highly symmetrical, making its flight efficiency largely unaffected by its current orientation. These characteristics are achieved by a novel drone design where six rotor arms align with the vertices of an octahedron, and where each arm can actively rotate along its long axis. Various standout features of MOMAV are presented: The high flight efficiency compared to arm configuration of other fully-actuated drones, the design of an original rotating arm assembly featuring slip-rings used to enable continuous arm rotation, and a novel control allocation algorithm based on sequential quadratic programming (SQP) used to calculate throttle and arm-angle setpoints in flight. Flight tests have shown that MOMAV is able to achieve remarkably low mean position/orientation errors of 6.6 mm, 2.1°(σ: 3.0 mm, 1.0°) when sweeping position setpoints, and 11.8 mm, 3.3°(σ: 8.6 mm, 2.0°) when sweeping orientation setpoints.
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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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