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Real-time shape estimation of Kirchhoff elastic rod based on force/torque sensor

机译:基于力/扭矩传感器的基尔霍夫弹性杆实时形状估计

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In this paper, we propose a real-time spatial shape estimation method for an elastic rod. Our proposed method does not use any image sensor nor shape sensor, but does use a six-axis force/torque sensor placed near one end of the elastic rod. In the proposed shape estimation method, the occlusion problem never occurs principally because the shape of a flexible object will be estimated based on an elastic rod model. We utilize the discretized Kirchhoff elastic rod for shape estimation, which can be viewed as a serial chain of rigid bodies connected with three-degree-of-freedom rotational spring joints. We show that real-time spatial shape estimation is possible based on real-time sensing of force/torque information. The computational time of the proposed shape estimation algorithm is linear in the number of rigid-body partition. Moreover, the required calculations are very simple owing to deep understanding of robot manipulator kinematics. Thus we can compute the spatial rod shape in realtime. We show experimental results in order to validate our proposed method.
机译:在本文中,我们提出了一种用于弹性杆的实时空间形状估计方法。我们所提出的方法不使用任何图像传感器和形状传感器,但是使用六轴力/扭矩传感器放置在弹性杆的一端附近。在所提出的形状估计方法中,遮挡问题永远不会主要发生,因为将基于弹性杆模型估计柔性物体的形状。我们利用离散的Kirchhoff弹性杆进行形状估计,这可以被视为与三维自由度旋转弹簧接头连接的刚体的串联链。我们表明,基于力/扭矩信息的实时感测,可以实现实时空间形状估计。所提出的形状估计算法的计算时间在刚体分区的数量中是线性的。此外,由于对机器人操纵仪运动学的深刻理解,所需的计算非常简单。因此,我们可以实时计算空间杆形状。我们显示实验结果,以验证我们提出的方法。

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