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Configuration Tracking for Soft Continuum Robotic Arms Using Inverse Dynamic Control of a Cosserat Rod Model

机译:软连续机械臂使用芯片杆模型的逆动态控制配置跟踪

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Controlling the configuration of a soft continuum robot arm is challenging due to the hyper-redundant kinematics of such robots. We propose a new model-based, inverse dynamic control approach to this problem that is defined on the configuration state variables of the geometrically exact Cosserat rod model. Our approach is capable of controlling a soft continuum robot to track static or time-varying 3D configurations through bending, torsion, shear, and extension deformations. The controller has a decentralized structure, in which the gain matrices can be defined in terms of the physical and material properties of distinct cross-sections of the robot arm. This structure facilitates its implementation on continuum robot arms composed of independently-controllable segments that have local sensing and actuation. The controller is validated with numerical simulations in MATLAB with a hydrogel-based soft robot arm that can produce the four primary types of deformations. The simulated arm successfully tracks these configurations with average normalized root-mean-square errors (NRMSE) below 7% in all cases. To demonstrate the generality of the control approach, its performance is also validated on a larger simulated robot arm made of silicone.
机译:控制软连续式机器人臂的配置是由于这种机器人的超冗余运动学而挑战。我们提出了一种新的基于模型的逆动态控制方法,在几何精确的Cosserat棒模型的配置状态变量上定义了这个问题。我们的方法能够通过弯曲,扭转,剪切和延伸变形来控制软连续式机器人以跟踪静态或时变3D配置。控制器具有分散结构,其中增益矩阵可以根据机器人臂的不同横截面的物理和材料特性来定义。该结构有助于其在连续式机器人臂上的实现,该臂组成具有局部传感和致动的可独立控制的段。控制器在MATLAB中验证了MATLAB中的数值模拟,其中水凝胶的软机器人臂可以产生四种主要类型的变形。模拟臂在所有情况下成功跟踪了平均归一化的根均线误差(NRMSE)的平均归一化的根均线误差(NRMSE)。为了展示控制方法的一般性,它的性能也在硅胶制成的较大模拟机器人臂上验证。

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