A Modeling Method Based on Koopman Operator Theory for Omnidirectional Mobile Manipulator System

The omnidirectional mobile robotic arm system is a highly coupled, multivariate, and highly nonlinear system. The traditional modeling approach uses Lagrange method to establish dynamic model, which suffers from issues of complex modeling, unknown model parameters, and insufficient accuracy in modeling. In this paper, a modeling method based on Koopman operator theory is proposed for this system, which is essentially a data-driven modeling method. Specifically, this paper collects data on system dynamic characteristics and transforms complex nonlinear models into high-dimensional linear models. This paper preprocesses the voltage data in the dataset based on platform characteristics and obtains the Koopman high-dimensional linear model, avoiding the complex modeling problems using Lagrange methods. Simulation has been performed, which confirms the accuracy and effectiveness of using Koopman operator theory for modeling omnidirectional mobile manipulators.