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基于ROS平台的串联攀爬机器人控制设计

Control Design of Serial Climbing Robot Based on ROS Platform
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摘要 该文基于ROS框架设计了一种五轴串联机器人的控制系统。控制器采用多核心控制模式,复杂计算与实时控制分开执行,提升了系统流畅性。采用遗传算法进行目标姿态求解,有效改善了原始矩阵逆解存在的弊端。此外,人机交互采用直接与间接的控制方式,通过将可视化工具Rviz与目标位姿求解算法相结合,实现了高效的机器人控制。实验结果表明,直接控制方式能够以较低的延迟实现快速响应和灵活控制,而间接控制方式虽牺牲了部分响应时间,却能通过简单的交互操作完成复杂的控制任务。总体而言,该研究为机器人在各种复杂环境下的应用提供了可靠的控制支持,具有重要的理论和实践意义。 In this paper,a five-axis series robot control system is designed based on ROS framework.The controller adopts multi-core control mode,and the complex calculation and real-time control are executed separately,which improves the system fluency.Genetic algorithm is used to solve the attitude of the target,which effectively improves the disadvantages of the original matrix inverse solution.In addition,the human-computer interaction adopts direct and indirect control methods,and the visualization tool Rviz is combined with the target pose solving algorithm to achieve efficient robot control.The experimental results show that the direct control method can achieve fast response and flexible control with low delay,while the indirect control method can complete complex control tasks through simple interactive operation although it sacrifices part of response time.In general,the research provides reliable control support for robot applications in various complex environments,and has important theoretical and practical significance.
作者 宋雨 王艳 吕淼 张昊博 SONG Yu;WANG Yan;LV Miao;ZHANG Haobo(School of Electrical and Information Engineering,Tianjin University,Tianjin 300072,China;Tianjin Development Zone Zhonghuan System Electronic Engineering Co.,Ltd.,Tianjin 300074,China;School of Electrical Engineering and Automation,Tianjin University of Technology,Tianjin 300384,China)
出处 《自动化与仪表》 2024年第6期62-66,71,共6页 Automation & Instrumentation
基金 国家自然科学基金项目(62103299)。
关键词 串联机器人 控制系统设计 人机交互 姿态求解 series robot control system design human-computer interaction attitude solving
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  • 1苏蕊.基于ARM芯片的嵌入式运动控制系统设计[J].微计算机信息,2008,24(11):137-138. 被引量:10
  • 2Najarian K, Splinter R. Biomedical signal and image process- ing[M]. Boca Raton, USA: CRC Press, 2012.
  • 3Yin Y H, Fan Y J, Xu L D. EMG and EPP-integrated human- machine interface between the paralyzed and rehabilitation ex- oskeleton[J], IEEE Transactions on Information Technology in Biomedicine, 2012, 16(4): 542-549.
  • 4George T, Shalu G K, Sivanandan K S. Sensing, processing and application of EMG signals for HAL (hybrid assistive lim- b)[C]//International Conference on Sustainable Energy and In- telligent Systems. Stevenage, UK: IET, 2011: 749-753.
  • 5Kasaoka K, Sankai Y. Predictive control estimating operator's intention for stepping-up motion by exo-skeleton type power assist system HAL[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems, vol.3. Piscataway, USA: IEEE, 2001: 1578-1583.
  • 6Kawamoto H, Lee S, Kanbe S, et al. Power assist method for HAL-3 using EMG-based feedback controller[C]//IEEE Inter- national Conference on Systems, Man and Cybernetics, vo1.2. Piscataway, USA: IEEE, 2003: 1648-1653.
  • 7Lee S, Sankai Y. Power assist control for walking aid with HAL- 3 based on EMG and impedance adjustment around knee joint [C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA: IEEE, 2002: 1499-1504.
  • 8Kiguchi K, Imada Y. EMG-based control for lower-limb power- assist exoskeletons[C]//IEEE Workshop on Robotic Intelligence in Informationally Structured Space. Piscataway, USA: IEEE, 2009: 19-24.
  • 9Fleischer C, Hommel G. A human-exoskeleton interface utiliz- ing electromyography[J]. IEEE Transactions on Robotics, 2008, 24(4): 872-882.
  • 10Chan F H Y, Yang Y S, Lam F K, et al. Fuzzy EMG classifica- tion for prosthesis control[J]. IEEE Transactions on Rehabilita- tion Engineering, 2000, 8(3): 305-311.

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