Task-Space Control of Continuum Robots using Underactuated Discrete Rod Models
Task-Space Control of Continuum Robots using Underactuated Discrete Rod Models
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DOI：
10.1109/iros47612.2022.9982271
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
D. C. Rucker;E. Barth;Josh Gaston;James C. Gallentine
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文献类型：
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作者：
D. C. Rucker;E. Barth;Josh Gaston;James C. Gallentine
柔性连续体机器人理论上具有无限多的自由度，但驱动器很少，欠驱动是控制柔性连续体机器人的核心挑战。然而，$m$致动器仍然可以用来控制一个动态软机器人在一个m维的输出任务空间。在本文中，我们开发了一个平面连续体机器人的任务空间控制方法，是强大的建模误差，需要很少的传感器信息。该控制器是基于一个高度欠驱动的离散杆力学模型在最大坐标，不需要转换到一个经典的机器人动力学模型的形式。这促进了简单的控制设计、实施和效率。我们对这个模型进行输入输出反馈线性化，应用滑模控制来增加鲁棒性，并制定一个观测器来估计稀疏输出测量的完整状态。仿真结果表明，即使存在显著的建模误差，不准确的初始条件，和输出只感测的任务空间的参考跟踪行为，可以实现精确的。
Underactuation is a core challenge associated with controlling soft and continuum robots, which possess theoreti-cally infinite degrees of freedom, but few actuators. However, $m$ actuators may still be used to control a dynamic soft robot in an m-dimensional output task space. In this paper we develop a task-space control approach for planar continuum robots that is robust to modeling error and requires very little sensor information. The controller is based on a highly underactuated discrete rod mechanics model in maximal coordinates and does not require conversion to a classical robot dynamics model form. This promotes straightforward control design, implementation and efficiency. We perform input-output feedback linearization on this model, apply sliding mode control to increase robustness, and formulate an observer to estimate the full state from sparse output measurements. Simulation results show exact task-space reference tracking behavior can be achieved even in the presence of significant modeling error, inaccurate initial conditions, and output-only sensing.