Design and analysis of a wall-climbing robot for passive adaptive movement on variable-curvature metal facades

IF 4.2 2区 计算机科学 Q2 ROBOTICS Journal of Field Robotics Pub Date : 2022-09-08 DOI:10.1002/rob.22118
Ze Jiang, Zhe Ma, Zhongjin Ju, Dianzheng Wang, Yundou Xu
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引用次数: 1

Abstract

To facilitate the safe adsorption and stable motion of robots on curved metal surfaces, a wall-climbing robot with a wheeled-type mobile mechanism that can passively self-adapt to walls with different curvature is proposed. The robot is composed of two relatively independent passive adaptive mobile mechanisms and overrunning permanent magnetic adsorption devices to achieve effective fitting of the driving wheels to the wall surface and adaptive surface motion. The overall design is based on a double-hinged connection scheme and gap-type permanent magnetic adsorption. The minimum adsorption force required for the robot to achieve stable climbing motion with no risk of slipping or capsizing is determined by developing a static analysis model. The effects of air-gap size and wall thickness on the adsorption force are analyzed by means of magnetic circuit design studies and parametric simulations on the permanent magnet adsorption device, as well as design optimization of the permanent magnet device. The motion performance test of the fabricated prototype shows that the robot can achieve adaptive curvature motion with self-attitude adjustment, and has a certain load capacity, obstacle crossing capability, and good surface adaptivity.

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变曲率金属外墙被动自适应爬壁机器人的设计与分析
为了促进机器人在弯曲金属表面上的安全吸附和稳定运动,提出了一种可被动自适应不同曲率墙壁的轮式移动机构爬壁机器人。该机器人由两个相对独立的被动自适应移动机构和超越式永磁吸附装置组成,实现驱动轮对壁面的有效贴合和自适应表面运动。整体设计采用双铰链连接方案和间隙式永磁吸附。通过建立静态分析模型,确定了机器人实现无滑倒或倾覆风险的稳定爬坡运动所需的最小吸附力。通过对永磁吸附装置的磁路设计研究和参数化仿真,分析了气隙尺寸和壁厚对吸附力的影响,并对永磁吸附装置进行了优化设计。样机的运动性能测试表明,该机器人能够实现自姿态调整的自适应曲率运动,具有一定的承载能力、越障能力和良好的表面自适应能力。
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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
期刊最新文献
Issue Information Cover Image, Volume 41, Number 8, December 2024 Issue Information Issue Information A CIELAB fusion-based generative adversarial network for reliable sand–dust removal in open-pit mines
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