Moving Horizon Estimation for Vehicle Robots using Partial Marker Information of Motion Capture System
Moving Horizon Estimation for Vehicle Robots using Partial Marker Information of Motion Capture System
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DOI：
10.1088/1742-6596/744/1/012049
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
M. Takahashi;K. Nonaka;K. Sekiguchi
中科院分区：
文献类型：
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作者：
M. Takahashi;K. Nonaka;K. Sekiguchi
使用运动捕捉相机的测量受到白噪声和异常值的波动。此外，被测量的标记物往往由于遮挡而无法被摄像机捕捉到，由于无法检测到足够数量的标记物，因此无法唯一地确定车辆的位置和航向角度。因此，需要一种鲁棒估计方法来抑制白噪声、离群点和遮挡的影响。在本研究中，我们引入了基于运动捕捉系统中部分标记信息的运动地平线估计（MHE）。利用评价范围内的标记信息和机器人动力学约束条件对目标函数进行优化。由于引入了约束条件，即使摄像机无法测量机器人的实际状态，其估计值也由MHE决定。这与我们之前的研究假设有足够数量的标记物是不同的。在本文中，即使隐藏了多个标记，我们也可以利用机器人上测量到的标记信息，通过MHE来估计车辆机器人的位置。我们将通过比较MHE和EKF来证明所提出方法的有效性。
The measurement using a motion capture camera is fluctuated by white noise and outliers. In addition, markers to be measured are frequently hidden from cameras by occlusion, then the position and heading angle of a vehicle cannot be uniquely determined because of failure to detect sufficient number of markers. Thus, robust estimation method is required which suppresses the influence of the white noise, the outlier and the occlusion. In this study, we introduce Moving Horizon Estimation (MHE) using partial marker information of motion capture system. It optimizes the objective function using both the marker information in the evaluation range and the constraints on the robot dynamics. By virtue of introduction of constraints, even if the cameras fail to measure the actual state of the robot, the estimated value is determined by MHE. It is the difference from our previous research which assumed that sufficient number of markers are available. In this paper, we estimate the position of the vehicle robot by MHE using the information of the measured markers on the robot, even if several markers are hidden. We will prove the effectiveness of the proposed method by comparing MHE with EKF.