Trajectory tracking control of slidable-wheel omnidirectional mobile robot based on linear model predictive control

Omnidirectional mobile robots with conventional wheels avoid the drawbacks (e.g., shock, slippage, and low load capacity) of omnidirectional mobile robots with wheels that have special structures. We previously proposed such a robot, called the slidable-wheel omnidirectional mobile robot (SWOM), as well as its controller for point-to-point movement. However, for practical applications, such as transporting goods in factories and warehouses, SWOM needs to be able to follow a predefined trajectory. In this paper, we present the design of a trajectory tracking controller for SWOM. Given that SWOM is a nonlinear system with constraints on both inputs and outputs, model predictive control (MPC) is adopted. Due to the high computational demands and time consumption associated with nonlinear MPC, linear MPC is used to achieve trajectory tracking. By expanding the previous research, an original method for generating a reference path that includes not only state variables but also inputs is proposed in this paper for the trajectory tracking task. The linearized kinematic model of SWOM is obtained using a first-order Taylor expansion around reference points on the reference path. Simulations considering slippage are conducted and the results show that SWOM can well track the reference path. Experiments conducted on a prototype also validate the effectiveness of the proposed control method.