基于力学的同心管机器人运动学模型在线参数估计

Cheongjae Jang, Junhyoung Ha, Pierre E Dupont, Frank Chongwoo Park
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引用次数: 7

摘要

虽然现有的同心管机器人基于力学的模型已经被实验证明可以近似实际运动学,但由于参数和可用测量之间的复杂关系,确定模型参数的准确估计仍然很困难。此外,由于基于力学的模型忽略了摩擦、非线性弹性和截面变形等现象,因此也不清楚模型误差是由于模型简化还是由于参数估计误差。这些机器人中使用的超弹性材料的参数可能是缓慢时变的,需要定期重新估计。本文提出了一种利用扩展卡尔曼滤波估计基于力学的模型参数的方法,作为在线参数估计的一步。通过仿真和实验验证了我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model.

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments.

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