This thesis applies flocking algorithms for the distributed consensus control of a multi-agent system composed of four-Mecanum-wheeled robots. The working mechanism of flocking is an artificial potential field consisting of attractive/repulsive forces and velocity alignment. The potential function of the attractive and repulsive force is introduced to control the connected distance among agents in the network. A consensus is a group of robots in a communication network to achieve common goals, which are the agreement of position and heading angle in this thesis. The main contribution of this thesis is our proposed feasible methods to achieve consensus control for general multi-agent systems of four-Mecanum-wheeled robots.With the fast development of information technology and the growing demand for data exchange around the world, the sensors and actuators of agents become more complicated and require more resources. Local communication among agents reduces the need for high material costs and lengthy installation time. This thesis established a controllable model of four-Mecanum-wheeled robots in a local communication network. An assumption is that all robots can obtain information on the relative position and heading angle difference between themselves and their neighbors. A few robots with installed GPS are directly connected to the central host. Our flocking methods under the assumed communication conditions adjust the velocities of robots by controlling the speed of Mecanum wheels.This thesis simulated the proposed leader-following flocking algorithms for cases of connected formation and snake formation with different numbers of leaders. The simulation results regarding the position consensus and heading angles consensus are provided to illustrate the robustness of the proposed algorithms.