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首页> 外文期刊>Robotica >Visual motor control of a 7DOF redundant manipulator using redundancy preserving learning network
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Visual motor control of a 7DOF redundant manipulator using redundancy preserving learning network

机译：使用冗余保留学习网络的7DOF冗余机械手的视觉电机控制

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摘要

This paper deals with the design and implementation of a visual kinematic control scheme for a redundant manipulator. The inverse kinematic map for a redundant manipulator is a one-to-many relation problem; i.e. for each Cartesian position, multiple joint angle vectors are associated. When this inverse kinematic relation is learnt using existing learning schemes, a single inverse kinematic solution is achieved, although the manipulator is redundant. Thus a new redundancy preserving network based on the self-organizing map (SOM) has been proposed to learn the one-to-many relation using sub-clustering in joint angle space. The SOM network resolves redundancy using three criteria, namely lazy arm movement, minimum angle norm and minimum condition number of image Jacobian matrix. The proposed scheme is able to guide the manipulator end-effector towards the desired target within 1-mm positioning accuracy without exceeding physical joint angle limits. A new concept of neighbourhood has been introduced to enable the manipulator to follow any continuous trajectory. The proposed scheme has been implemented on a seven-degree-of-freedom (7DOF) PowerCube robot manipulator successfully with visual position feedback only. The positioning accuracy of the redundant manipulator using the proposed scheme outperforms existing SOM-based algorithms.
机译：本文讨论了冗余机械手的视觉运动控制方案的设计和实现。冗余机械手的逆运动学映射是一对多的关系问题。即，对于每个笛卡尔位置，多个关节角度向量被关联。当使用现有的学习方案学习了这种逆运动学关系时，尽管机械手是多余的，但仍可获得单个逆运动学解决方案。因此，提出了一种基于自组织图（SOM）的新的冗余保存网络，以利用联合角度空间中的子簇学习一对多关系。 SOM网络使用三个标准来解析冗余，即懒臂运动，最小角度范数和图像雅可比矩阵的最小条件数。所提出的方案能够在不超过物理关节角度限制的情况下，将操纵器末端执行器导向1毫米定位精度内的所需目标。引入了一种新的邻域概念，以使操纵器能够遵循任何连续的轨迹。该方案已在仅具有视觉位置反馈的七自由度（7DOF）PowerCube机器人操纵器上成功实施。使用提出的方案的冗余机械手的定位精度优于现有的基于SOM的算法。

著录项

  • 来源
    《Robotica》 |2010年第6期|P.795-810|共16页
  • 作者

    Swagat Kumar; rnPremkumar P.; rnAshish Dutta; Laxmidhar Behera;

  • 作者单位

    Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India;

    rnDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India;

    rnDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India;

    rnDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India School of Computing and Intelligent systems, University of Ulster, Magee, Northern Ireland, UK;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    visual motor control; self-organizing map; sub-clustering; redundancy resolution; inverse kinematics;

    机译：视觉电机控制;自组织图;子集群冗余解决方案;逆运动学;

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