Design and Control of a Reconfigurable Robot with Rolling and Flying Locomotion

IF 2.2 3区 工程技术 Q2 ENGINEERING, MECHANICAL Actuators Pub Date : 2024-01-09 DOI:10.3390/act13010027
Qing Chang, Biao Yu, Hongwei Ji, Haifeng Li, Tiantian Yuan, Xiangyun Zhao, Hongsheng Ren, Jinhao Zhan
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Abstract

Given the continual rise in mission diversity and environmental complexity, the adept integration of a robot’s aerial and terrestrial locomotion modes to address diverse application scenarios has evolved into a formidable challenge. In this paper, we design a reconfigurable airframe robot endowed with the dual functionalities of rolling and flying. This innovative design not only ensures a lightweight structure but also incorporates morphing capabilities facilitated by a slider-crank mechanism. Subsequently, a land-to-air transformation strategy for the robot is introduced, achieved through the coordinated movement of the robotic arm and the servo motor. To ensure stable control of the robot amid external wind disturbances, we leverage the collaboration between a Generative Adversarial Network (GAN)and a Nonlinear Model Predictive Control (NMPC) controller. After the wind force magnitude is predicted through the neural network, the robot’s adeptness in flexible trajectory tracking is verified. Under simulated wind conditions of 12.1 m/s, the trajectory error consistently remains within the range of 10–15 cm, affirming the effectiveness of this control method.
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具有滚动和飞行运动功能的可重构机器人的设计与控制
鉴于任务的多样性和环境的复杂性不断增加,如何巧妙地整合机器人的空中和地面运动模式以应对不同的应用场景已演变成一项艰巨的挑战。在本文中,我们设计了一种具有滚动和飞行双重功能的可重构机身机器人。这种创新设计不仅确保了结构的轻量化,还通过滑块-曲柄机制实现了变形功能。随后,通过机械臂和伺服电机的协调运动,介绍了机器人从陆地到空中的转换策略。为了确保机器人在外部风力干扰下的稳定控制,我们利用了生成对抗网络(GAN)和非线性模型预测控制(NMPC)控制器之间的协作。通过神经网络预测风力大小后,机器人的灵活轨迹跟踪能力得到了验证。在 12.1 米/秒的模拟风速条件下,轨迹误差始终保持在 10-15 厘米的范围内,肯定了这种控制方法的有效性。
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来源期刊
Actuators
Actuators Mathematics-Control and Optimization
CiteScore
3.90
自引率
15.40%
发文量
315
审稿时长
11 weeks
期刊介绍: Actuators (ISSN 2076-0825; CODEN: ACTUC3) is an international open access journal on the science and technology of actuators and control systems published quarterly online by MDPI.
期刊最新文献
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