基于软测量的可重构模块机器人分散力/位置控制

Decentralized Force/Position Control for Reconfigurable Modular Robot Based on Soft Sensor

在受限空间内,可重构模块机器人末端腕力传感器造价昂贵且易受环境影响,它的使用还提高了机器人在软硬件设计上的复杂程度,针对这一问题,提出了基于软测量的可重构模块机器人分散力/位置控制方法。将可重构模块机器人系统在各个方向上进行模型分解,各方向的模型看作一个子系统,利用自适应RBF神经网络去估计各子系统间的不确定项和耦合关联项。在末端未安装腕力传感器的情况下,利用自适应RBF神经网络去估计末端接触力,并推导出了RBF神经网络的权值、径向基函数中心和宽度的自适应律。2类不同自由度可重构模块机器人的仿真结果验证了所提方法的有效性。

In constrained space, the wrist force sensor of reconfigurable modular robot is expensive and easily affected by environment, it also increased the complexity of the robot used in software and hardware design, so in order to solve this problem, the force/position control method for reconfigurable modular robot based on the soft sensor is proposed. First, the model of the reconfigurable modular robot system was decomposed in all directions. The model in each direction was considered as a subsystem, and the adaptive RBF neural network was used to estimate the uncertainty and coupling relation among subsystems. Then, in the end was not installed the sensor's case, the adaptive RBF neural network was used to estimate the contact force, and the weights of the adaptive RBF neural network, adaptive laws of centers and widths of radial basis function were derived. Finally, the simulation results of 2 kinds of reconfigurable modular robots with different degrees of freedom (DOF) verify the effectiveness of the proposed method.