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Leader-Following Formation Tracking Control of Mobile Robots Without Direct Position Measurements

机译:没有直接位置测量的移动机器人的领导者跟随编队跟踪控制

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摘要

Most existing formation control approaches assume that accurate global or local position measurements of the robots are directly available, without giving details about how to obtain these measurements, or only providing Kalman filter-type estimators to get them without considering effects of the estimation on the closed-loop system stability. Hence, developing formation controllers with position estimators that can guarantee overall closed-loop system stability becomes highly desirable. This technical note presents a new formation tracking controller for the nonholonomic mobile robots without using direct position measurements. To deal with the absence of accurate position measurements, feedback information from a perspective camera, the odometry and Attitude and Heading Reference System (AHRS) sensors is used to design an observer to provide online estimates of the relative position of the follower with respect to the leader. Using Lyapunov stability analysis, we show that the combined observer-controller closed-loop system is stable, and both the formation tracking errors and the relative position estimation errors asymptotically converge to zero. The performance of the proposed scheme is illustrated through experimental results.
机译:大多数现有的编队控制方法都假定可以直接获得准确的机器人全局或局部位置测量值,而没有提供有关如何获取这些测量值的详细信息,或者仅提供卡尔曼滤波器类型的估算器来获取它们,而无需考虑估算值对封闭式系统的影响。回路系统的稳定性。因此,迫切需要开发具有位置估计器的地层控制器,以保证整个闭环系统的稳定性。本技术说明介绍了一种用于非完整移动机器人的新型编队跟踪控制器,无需使用直接位置测量。为了解决缺少精确位置测量的问题,需要使用来自透视相机,里程计和姿态和航向参考系统(AHRS)传感器的反馈信息来设计观察者,以在线提供跟随者相对于行走者的相对位置的估计值领导。使用Lyapunov稳定性分析,我们表明观察者-控制器组合的闭环系统是稳定的,并且编队跟踪误差和相对位置估计误差都渐近收敛于零。实验结果说明了该方案的性能。

著录项

  • 来源
    《Automatic Control, IEEE Transactions on》 |2016年第12期|4131-4137|共7页
  • 作者单位

    Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong;

    Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong;

    Department of Automation, Shanghai Jiao Tong University, Shanghai, China;

    Department of Automation, Shanghai Jiao Tong University, Shanghai, China;

    College of Information Engineering, Zhejiang University of Technology, Hangzhou, China;

    State Key Laboratory of Fluid Power Transmission and Control, Department of Mechanical Engineering, Zhejiang University, Hangzhou, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mobile robots; Position measurement; Estimation; Cameras; Robot vision systems;

    机译:移动机器人位置测量估计相机机器人视觉系统;

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