A Semilinear Parameter-Varying Observer Method for Fabric-Reinforced Soft Robots.
A Semilinear Parameter-Varying Observer Method for Fabric-Reinforced Soft Robots.
复制标题
DOI：
10.3389/frobt.2021.749591
复制
发表时间：
2021
影响因子：
3.4
通讯作者：
Schultz JA
中科院分区：
文献类型：
--
作者：
Bui PDH;Schultz JA
本文提出了一种观测器体系结构，可以估计织物增强充气软机器人的组态空间变量、它们的变化率和接触力。我们将连续机器人离散成一系列由不可扩展螺纹连接的圆盘；这使得在描述机器人的行为时具有很大的灵活性。首先，系统动力学由线性参数变化（LPV）模型描述，该模型包括一组子系统，每个子系统对应于一个特定的腔室压力范围。我们面临的一个现实挑战是，物理机器人原型呈现出一个滞回线，其方向取决于腔体是充气还是放气。本文将迟滞模型转换为半线性模型，以避免时间逆定义，使其适合于观测器和控制器的设计。描述软体机器人的最终模型，包括离散连续体和迟滞行为，称为半线性变参模型。半线性变参数观测器结构包括一组子观测器，对应于SPV模型中每个腔室压力范围的子系统。通过仿真和实验对所提出的观测器进行了评价。仿真结果表明，该观测器能够估计出构型空间变量及其变化率，且无稳态误差。此外，实验结果显示广义接触力估计的快速收敛性以及相对于地面真实运动捕获数据的机器人构型的良好跟踪。
This paper presents an observer architecture that can estimate a set of configuration space variables, their rates of change and contact forces of a fabric-reinforced inflatable soft robot. We discretized the continuum robot into a sequence of discs connected by inextensible threads; this allows great flexibility when describing the robot’s behavior. At first, the system dynamics is described by a linear parameter-varying (LPV) model that includes a set of subsystems, each of which corresponds to a particular range of chamber pressure. A real-world challenge we confront is that the physical robot prototype exhibits a hysteresis loop whose directions depend on whether the chamber is inflating or deflating. In this paper we transform the hysteresis model to a semilinear model to avoid backward-in-time definitions, making it suitable for observer and controller design. The final model describing the soft robot, including the discretized continuum and hysteresis behavior, is called the semilinear parameter-varying (SPV) model. The semilinear parameter-varying observer architecture includes a set of sub-observers corresponding to the subsystems for each chamber pressure range in the SPV model. The proposed observer is evaluated through simulations and experiments. Simulation results show that the observer can estimate the configuration space variables and their rate of change with no steady-state error. In addition, experimental results display fast convergence of generalized contact force estimates and good tracking of the robot’s configuration relative to ground-truth motion capture data.
登录
查看更多内容
影响因子：
10.2
作者：
MACKI, JW;NISTRI, P;ZECCA, P
通讯作者：
ZECCA, P
影响因子：
6.8
作者：
Oh, JH;Bernstein, DS
通讯作者：
Bernstein, DS
影响因子：
7.9
作者：
Connolly, Fionnuala;Polygerinos, Panagiotis;Bertoldi, Katia
通讯作者：
Bertoldi, Katia
影响因子：
2.1
作者：
Levant, A
通讯作者：
Levant, A
影响因子：
6.4
作者：
Levant, A
通讯作者：
Levant, A