In recent years, trajectory tracking of a mobile robot has been one of the most addressed problems in the specilized literature, as a mobile robot must have the ability to follow a trajectory, while also compensating various external and internal disturbances. This paper proposes an IEHO-STSM controller based on the super-twisting sliding mode for the path tracking of a mobile robot. First, a new improved IEHO algorithm has been developed and introduced, based on the EHO (Elephant Herding Optimization) metaheuristic algorithm. The developed algorithm consisted in improving the performance of the basic EHO such as convergence speed, exploration and exploitation capabilities. Then, based on a dynamic model of the mobile robot, a super-twisting sliding mode (STSM) controller was designed to guide the robot to the desired trajectory. Finally, the improved IEHO algorithm was applied for adjusting the parameters of the super-twisting sliding mode (STSM) controller. The analysis of the proposed IEHO algorithm has been done by comparing it with EHO, PSO (Particle Swarm Optimization) and GWO (Grey Wolf Optimizer) algorithms, by employing it in tuning the STSM. The simulation results show that the proposed IEHO-STSM can reach both high precision and high speed capability, by overcoming external and internal disturbances.