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    method and present results in a small humanoid robot
    head, calibrating its eyes and neck. Notwithstanding, the
    method can be easily extended for other serial kinematics
    structures.
    This paper is organized as follows. In Section II we
    formulate the problem in terms of the system kinematics
    and an homography estimation problem. Then, in Section
    III we address the problem of estimating the particular
    homography arising in this problem. Section IV is devoted
    to the presentation of experimental results in the automatic
    calibration of a small robot head. Finally, Section V
    presents the conclusion of the work and directions for
    future developments.
    II. PROBLEM FORMULATION
    In this section we formulate our problem in terms of
    an homography estimation problem. An homography is
    a transformation that is able to explain the relationship
    between the points observed in an image before and after
    a rotation of the camera. From the homography it is
    often possible to recover the rotation angles. Therefore,
    we are going to analyze the homography arising from the
    prospective motions applied to the robot, as a function of
    the initial, unknown, joint angles.
    Let us consider the tilt-pan kinematics structure pre-
    sented in Fig. 1. A camera is attached first to a pan unit,
    and then the pan unit is attached to a tilt unit. A similar
    analysis can be made for other kinematics structures.Considering identical reference coordinate frames for all
    joints in the canonical state, as shown in Fig. 1, the rotation
    matrix representing the camera’s orientation with respect
    to the world reference frame depends on the pan and tilt
    angular displacements, and is given by:Xc
    Let us consider that, at start-up, the system has initial
    angles 0
    t and 0
    p. These angles are unknown when the
    system is turned on. Then, a prospective motion of the tilt
    unit is performed: the tilt angle is changed by t. This
    process is illustrated in Fig. 2. For the sake of simplicity,
    and without loss of generality, we can consider a null
    initial tilt angle, 0
    t = 0. This corresponds to set the world
    reference frame aligned with the initial robot’s tilt frame.概述:随着微型机器装置的增加,有些促动器不提供绝对位置感应器,因此让系统在启动时未知。在这篇论文中我们提出了一个基于视觉的方法串口云台的运动结构,自动校准对末端执行器的透视相机。这种系统的例子有监控摄像头和人形机器人的头。这种方法基于在一个关节运动链的前瞻性运动诱导摄像机图像中的运动。单应性矩阵的分析允许其他关节角度计算。该方法可迭代多轴校准较长序列的链组成的旋转接头。该方法需要校准的相机,但运行完全自动化。我们已实施和验证的方法,在一个小的仿人机器人头部。论文网
    一.    介绍
    每当在机器人系统中的电机不具有绝对的传感器,它是不可能知道在启动状态的机器人。这经常发生,因为大多数汽车都配备了增量编码器作为反馈传感器,缺乏绝对位置传感。因此,一个程序集机器人到一个已知的初始状态是必要的,这削弱了它的原点,或零位置。为了解决这个问题,机器人是通常的装备是限位开关、或原点的开关,检测时,轴特别是角位置。然而,由于小型化的约束,它可能无法在机器人内安装传感器。另一种可能性是传动轴机械停止监控电机电流。当电流超过一定值,则电动机已达到机械限位,其角度可称为先验的。然而,长期的在本程序添加一个物理应激源的系统,有可能损坏机械部件。
    即使上述策略是可行的,他们需要精心的布置限制和总开关,和精确的测量的机械限制。此外,当连接相机到末端,总有一些误差,可降解的初始校准程序。
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