Unscented Kalman Filter and 3D vision to improve cable driven surgical robot joint angle estimation
Unscented Kalman Filter and 3D vision to improve cable driven surgical robot joint angle estimation
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DOI：
10.1109/icra.2016.7487606
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发表时间：
2016-05
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影响因子：
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通讯作者：
M. Haghighipanah;Muneaki Miyasaka;Yangming Li;B. Hannaford
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文献类型：
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作者：
M. Haghighipanah;Muneaki Miyasaka;Yangming Li;B. Hannaford
索驱动机械手由于其紧凑的设计、低惯性和远程驱动而在手术机器人中很受欢迎。在这些机械手中，编码器通常安装在电机上，关节角度估计的基础上传输运动学。然而，由于电缆的非线性特性，如电缆拉伸，较低的刚度，和运动学模型参数的不确定性，关节角度估计的精度是有限的，与传动运动学方法。为了提高这些机械手的定位，我们使用一对低成本的立体摄像机作为观察关节角度，我们将这些噪声测量输入到无迹卡尔曼滤波器（UKF）进行状态估计。我们使用双UKF离线估计电缆参数和状态。我们评估了所提出的方法的有效性乌鸦-II实验手术研究平台上。联合输出处的附加编码器被用作参考系统。实验结果表明，UKF算法将联合角度估计精度提高了33- 72%。此外，我们还测试了摄像机遮挡情况下状态估计的可靠性。我们发现，当系统动态调整离线UKF参数估计，摄像机遮挡在线状态估计没有影响。
Cable driven manipulators are popular in surgical robots due to compact design, low inertia, and remote actuation. In these manipulators, encoders are usually mounted on the motor, and joint angles are estimated based on transmission kinematics. However, due to non-linear properties of cables such as cable stretch, lower stiffness, and uncertainties in kinematic model parameters, the precision of joint angle estimation is limited with transmission kinematics approach. To improve the positioning of these manipulators, we use a pair of low cost stereo camera as the observation for joint angles and we input these noisy measurements into an Unscented Kalman Filter (UKF) for state estimation. We use the dual UKF to estimate cable parameters and states offline. We evaluated the effectiveness of the proposed method on a Raven-II experimental surgical research platform. Additional encoders at the joint output were employed as a reference system. From the experiments, the UKF improved the accuracy of joint angle estimation by 33- 72%. Also, we tested the reliability of state estimation under camera occlusion. We found that when the system dynamics is tuned with offline UKF parameter estimation, the camera occlusion has no effect on the online state estimation.